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Joe McKendrick

Joe McKendrick

Joe McKendrick is a contributing editor and writer to Database Trends and Applications and Big Data Quarterly magazines, as well as lead research analyst for Unisphere Research at Information Today, Inc.

Articles by Joe McKendrick

KDNuggets, a community site for data professionals, ranked "We Don't Need Data Scientists, We Need Data Engineers," by Mihail Eric, a venture capitalist, researcher, and educator, as its top story of 2021. This sentiment holds even more true today, especially with the unending rush to leverage both generative and predictive AI within enterprise operations. Without the right kind of data, AI is dead in the water.

Posted August 15, 2024

With today's data-driven practices and AI demands, there has never been more pressure on data managers and professionals to deliver real-time, high-quality information when and where it is needed. Many organizations are struggling to achieve such a level of "data management maturity," in which data is provided on an agile, automated basis.

Posted August 08, 2024

In many organizations, microservices have become the default method of application building and deployment, leveraging containers and Kubernetes. The resulting architecture has been a flexible network of services that provide resiliency by operating independently, unaffected by potential failures in other parts of the system. Recently, however, some technology leaders have been questioning if this is the best way to build.

Posted August 08, 2024

Two surveys show that many executives are skeptical they can move forward with AI demands, which include the right data, at the right time. AI is a high priority, and is in production at most sites, but supplying trustworthy data is still a challenge at the back end.

Posted June 13, 2024

Never before has the business spotlight been on database managers and professionals as it is at this time. Every business leader now wants a data-driven organization, as they recognize this is the key to competitive differentiation. Data monetization is seen as a vast new revenue source. AI—both operational and generative—relies on effective data management and quality. The ongoing transition to digital business demands real-time delivery of insights to end users and applications.

Posted June 13, 2024

AI has become pervasive across enterprises, and the drive is now on to push this potentially powerful intelligence out to the edge and network, where it can deliver insight and operational performance in real time. These days, no discussion of edge and IoT is complete without weighing the implications of AI. "If people think AI will stop at data centers, they have an unfortunate blind spot, because AI is likely to be deployed in some form at the edge," said Kevin Brown, SVP at Schnei­der Electric. "In my opinion, it will bring with it a host of new challenges regard­ing data privacy concerns, an increasing demand for power, and an infrastructure that will be even more broadly distrib­uted. Undoubtedly, we need to get ahead of these challenges."

Posted June 05, 2024

Data makes the world go round, but there are gaps in the data needed to make the products and raw materials that move around the world. Unforeseen events around the globe—such as weather, wars, ships running aground, or infrastructure issues such as the Francis Scott Key Bridge collapse that closed the main shipping lane in and out of the Port of Baltimore—can wreak havoc with even the most carefully planned supply chains.

Posted April 11, 2024

Data management needs AI and machine learning (ML), and, just as important, AI/ML needs data management. As of now, the two are connected, with the path to suc­cessful AI "intrinsically linked to modern data manage­ment practices," said Dan Soceanu, senior product manager for AI and data management at SAS. Blazing this path requires "pri­oritizing data quality, accessibility, and governance."

Posted April 11, 2024

AI—both operational and generative—is knocking on enterprises' doors, forcing data managers to make new architectural choices on what it will take to support these data-hungry initiatives. Data mesh and data fabric are increasingly favored to help organizations get better control of their data, but which is the best option?

Posted April 10, 2024

Both operational and generative AI depend on distilling reliable data sources. A new survey, however, finds they are being overwhelmed by data sources and providing the data needed to deliver insights. In a survey of 600 chief data officers and data professionals released by Informatica, 41% admit they're juggling 1,000 or more data sources. A number, 79%, expect to increase in 2024.

Posted February 08, 2024

The momentous transformation putting data managers and their systems at the helm of modern enterprises has only begun. Industry leaders and experts agree that it's critical for data managers and team leaders to design today's data architectures to meet the demands of a digital economy, from cloud to real-time streaming to AI.

Posted February 08, 2024

Data managers, administrators, engineers, and analysts know more than anyone what kind of data is available to enterprises seeking to compete in the AI and analytics age. However, their perceptions of data quality are slipping—even though data quality has increased in importance due to the rise of analytics, AI, IoT, data monetization, and other next-generation initiatives.

Posted January 11, 2024

In the year ahead, data managers and their enterprises will be at a crossroads. Organizations will be leaning more heavily than ever on data—and the teams that manage it—for success with their customers, markets, and operations. The world of data is changing rapidly, and with it, its role in the business, from sitting on databases in the back end to competitive differentiation. Data is driving everything, everywhere.

Posted January 11, 2024

Data, the potent fuel powering the AI-driven enterprise, is always on the move, as are the tools, technologies, and techniques being employed to manage and deliver it. With the intense emphasis on AI and machine learning these days, it's urgent to ensure that data is available, timely, accurate, and relevant. That means no letup with efforts to ensure data pipelines are flowing unimpeded. With so much at stake, we canvassed industry leaders and experts on what challenges lie ahead and how to address them. Here are some leading issues:

Posted December 18, 2023

For most enterprises these days, hyperscale data workloads and AI have become the norm and are driving data strategies. However, while conventional wisdom dictates that this means greater reliance on cloud services and cutting-edge approaches to manage data pipelines, there's a place for more well-tread approaches as well. Many data managers intend to beef up their data warehouse capabilities and even return to on-prem systems in the near future.

Posted October 12, 2023

It may be well-understood that cybersecurity needs to be front and center in all technology projects, but organizations are still slow or hesitant to fully commit to it. This is becoming a problem for data-intensive organizations, which need to brace for an onslaught of both external and internal threats. Only about one-half of organizations are beginning to recognize how important cybersecurity is from the start in any transformation effort, an Accenture survey of 3,000 executives shows.

Posted October 12, 2023

The "big data" world is pervasive—to the point in which every organization is now a big data organization. As AI, machine learning, and other high-end analytics become mainstream parts of business operations, new ways of handling data assets are coming to the fore. Industry leaders and experts recently shared their views with Big Data Quarterly on the latest technology developments shaping today's big data world.

Posted October 10, 2023

Existing data infrastructures are crumbling under the weight of data, leading to unsustainable energy consumption, increased management complexity, and declining security. That's the word from a recent survey of 1,288 executives, released by Hitachi Vantara. The survey also finds 76% feel their current data infrastructures "will be unable to scale to meet upcoming demands"—such as AI. Another 61% report they are simply "overwhelmed" by the amount of data they manage. By 2025, the report's authors predict, large organizations will be storing more than 65 petabytes (PB) of data.

Posted August 10, 2023

For more and more organizations, real time is not only the right time—it's the only time that matters. No longer can decision makers afford to only understand the material events affecting their businesses a month, a day, or even just a few hours after the fact. They need a sense of what is happening in the moment to be able to predict and adjust for events that are arising. The value of real-time data "is that it provides needed information to accelerate business insights so teams can make better informed decisions and avoid the issues around using older data," said Tarun Chopra, vice president of product management for data and AI at IBM.

Posted August 10, 2023

The technology pendulum has long been swinging between centralization versus decentralization. Is it better to have a mainframe or distributed systems and data across Windows, Linux, and Unix platforms? Is it better to have these server farms or consolidate things with a cloud provider? Now, the action is moving away from the cloud, toward edge and Internet of Things (IoT) configurations. The enterprise market for edge computing will grow by 22% over the coming year, mainly for hardware, according to estimates from Deloitte Global. By contrast, enterprise networking equipment expenditures will grow by 4%, while overall enterprise IT spending is projected to rise by 6%.

Posted June 14, 2023

The issue of data silos has long hamstrung the efforts of data managers and their business counterparts to get an accurate, real-time picture of their enterprises. Now, a recent study suggests that open source technologies and data cloud platforms are helping to clear up these silos. Is this finally the long-sought, silo-busting holy grail?

Posted June 08, 2023

There's no question that this year, we're seeing dramatic upheavals in the data and analytics space. AI, of course, is the subject du jour, but any discussion of AI and its potential must, by necessity, involve the data teams that provide the information that makes AI successful. Here are what industry leaders and experts see as the most important technologies shaping the growth of data-driven enterprises.

Posted June 08, 2023

Low-code and no-code development has become a critical component of enterprise technology landscapes. Gartner predicts that within the next 3 years, developers outside IT departments will account for at least 80% of the userbase for low-code development tools, up from 60% in 2021. Low- and no-code offers opportunities to offload coding and integration work to business users, relieving burdened IT departments.

Posted April 20, 2023

Just a few years ago, no one would have imagined running their SQL Server databases on anything other than Windows Server. Now, with companies requiring data-driven capabilities for a range of needs, the idea of running SQL Server on a non-Windows platform has become almost commonplace—whether on open-source operating systems or in the cloud.

Posted April 13, 2023

Are we finally seeing the democratization of artificial intelligence (AI)?  New research out of OpenAI and the University of Pennsylvania suggests that generative AI, thanks to open and widely available tools such as ChatGPT (Generative Pre-trained Transformer) models and GPT-4, will be part of the jobs of at least 80% of occupational groups.

Posted April 13, 2023

Data analytics—and the people who make it happen—has emerged as the centerpiece of enterprises as they advance through the turbulent months ahead. Many of these eff­orts are gelling around the formation of dedicated C-level leaders, such as chief data officers and chief data analytics officers (CDOs and CDAOs, respectively).

Posted February 09, 2023

While the emerging constellation of next-generation data architectures—fabric, mesh, and cloud—is extremely appealing, it's still full of unknowns. ­These approaches present opportunities for greater data democratization, but also increased complexity. Understanding the distinctions between data fabric and mesh are also important before moving to this architecture.

Posted February 09, 2023

Moving to the cloud may seem, on its surface, a good way to better manage the quality and viability of data resources for enterprises. However, as data accelerates its move to the cloud, the complexity involved in assuring quality and viability has only increased.

Posted January 12, 2023

Uncertain economic conditions, skills shortages, rising automation, increasing regulation, and digital disruption—all add up to a stew of both challenges and opportunities for data managers in the year ahead. Emerging technologies—and new attitudes—are reshaping the look and scope of the information management landscape, with implications for overall business strategies and individual careers alike.

Posted January 12, 2023

To say the past year has been interesting for data managers and professionals is an understatement. Intensifying efforts to achieve data-driven processes, escalating security issues, shifts toward graph and cloud databases, and supply chain turbulence have dominated data teams' task lists. The coming year will be no different.

Posted December 13, 2022

Is it getting easier or more difficult to lock down data in today's digital enterprises? Industry leaders have mixed opinions on the state of that challenge. Cloud vendors promise industrial-grade security for backend applica­tions and data, while at the same time the move to cloud increases complexity.

Posted October 06, 2022

Software audits—in which vendors probe enterprise customer imple­mentations for overuse of licenses or unauthorized installations—are becoming a big business—and an emerging source of revenues. Whether on-premises or accessing services through the cloud, many companies report having been the subject of software audits, often resulting in tens of thousands of dollars of assessments.

Posted October 06, 2022

The big data world is changing in ways never seen before, particularly when it comes to bringing data together and into situations where it can be actionable for the business. The challenge faced by all enterprises—large and small—is being able to discover, identify, and bring the data needed to build products, deliver services, and understand customers. Data integration itself has been a practice—and challenge—for decades. Now, however, new tools and processes are enabling new ways of bringing enterprises to a state in which it can support sophisticated applications such as artificial intelligence, machine learning, and the Internet of Things.

Posted September 27, 2022

These days, data managers have an embarrassment of riches when it comes to the platforming, storage, and provisioning of data and associated analytics applications. However, selecting the right environment for pressing business needs can be confusing and overwhelming. The key is understanding how to map the right technologies to the business problems or opportunities at hand.

Posted August 11, 2022

The data lakehouse, data fabric, and data mesh, are no longer just dreams shared by analysts at conference presentations. A new survey of more than 200 IT leaders by Unisphere Research, a division of Information Today, Inc., finds considerable uptake of these modern data architectures. "The Move to Modern Data Architecture: 2022 Data Delivery and Consumption Patterns Survey," May 2022, was conducted in partnership with ChaosSearch and included input from directors/managers of IT, directors/managers of analytics, and data architects.

Posted August 11, 2022

As we advance deeper into the digitally roaring 2020s, data executives and profession­als are seeing change on a scale never seen before in their careers. A new generation of technologies that often build on previous solutions means new ways of working and ensuring performance for today's increasingly data-driven enterprises. We asked industry leaders for their views on what technology is enhancing enterprises' ability to compete on data.

Posted June 02, 2022

With greater automation and more robust cloud services, today's data professionals are seeing their roles elevated, working more closely with their businesses to deliver data-driven capabilities. At the same time, they, too, are feeling the effects of "The Great Resignation," reporting higher-than-usual turnover and increased pressure on overworked staffs.

Posted June 02, 2022

The case for increased data automation is clear. "Data teams are spending significant amounts of time on service requests like infrastructure, user provisioning, and incident coordination and communication," said Tina Huang, CTO and founder of Transposit. "Teams today are often manually creating tickets, Slack channels, and Zoom meetings, plus communicating with stakeholders. Data teams must ensure internal customers using data have access to the data they need and real-time updates about interferences with that data." Other tasks ripe for automation include log parsing, correlation, permissions and access, and more.

Posted May 16, 2022

Enterprises are just scratching the sur­face of data-driven opportunities, and many simply aren't ready to leverage their data assets to lead their markets. There are concerns about the security of sharing data between organizations, as well as iden­tifying and building platforms to accomplish a data-driven infrastructure. These concerns may abate as data-driven partner ecosystems and benefits develop. 

Posted April 07, 2022

As everyone pushes for real-time analytics, more responsive online services, and more protection against cybercrime, data resiliency has moved front and center. Put simply, data must be available at all times. This requires a shift in con­ventional thinking toward data resiliency strategies in rec­ognition of the fact that it is no longer a technical issue; it's a business issue.

Posted April 07, 2022

With the push to automate increasingly complex data environments, along with a greater need to spur collaboration to deliver more effective and timely analytics capabilities, organizations are turning to DataOps as well as a series of related "Ops" methodologies. Will DataOps—eventually conjoined with DevOps, AIOps, and MLOps—help businesses compete in the digital era? Industry observers point out that these approaches are promising, but a lot of work lies ahead to achieve true collaborative and automated innovation in the data management space.

Posted April 01, 2022

Data management has never been so unfettered—and yet so complicated at the same time. An emerging generation of tools and platforms is helping enterprises to get more value from their data than ever. These solutions now support and automate a large swath of structural activities, from data ingestion to storage, and also enhance business-focused operations such as advanced analytics, AI, machine learning, and continuous real-time intelligence.

Posted February 08, 2022

The costs of downtime—even for a minute—are simply too steep for today's digitally evolving enterprises to tolerate. As part of their efforts to keep expensive downtime at bay—and ensure the continued viability and availability of data—data managers are increasingly turning to strategies such as automation and cloud services. Still, they continue to have difficulties and acknowledge that keeping their data environments up-to-date is holding them back from delivering more capabilities to their organizations.

Posted February 08, 2022

Becoming a data-driven enterprise isn't just a lot of analyst hyperbole. It is the ability to deliver tangible results, from successfully launching new products to achieving increased productiv­ity. A recent study of 1,250 executives, con­ducted by the Enterprise Strategy Group and Splunk, reveals that data leaders—those organizations that are excelling at data clas­sification, aggregation, quality measures, investigation skills, and monitoring—are seeing results in their bottom lines and mar­ket positions. At the same time, the survey shows, all organizations still lag in moving forward with data aggregation, classification, and monitoring.

Posted December 08, 2021

The past 2 years have been defining ones for enterprises seeking to become data-driven. There have been changes wrought by COVID-19, of course, but, even before the pandemic, companies were already on a path to better leverage the data that was streaming in from all corners of their orga­nizations. With this heightened focus, new roles have been emerging for the caretakers of data, including database administrators, data engineers, data analysts, data scientists, and developers.

Posted December 08, 2021

AI, machine learning, and edge com­puting may be all around us, and these technology endeavors all have one important thing in common: Their suc­cess depends on the quality of the data fed into them. Data managers recognize that data quality efforts must be improved to meet these new demands and they are con­cerned about the quality of the data moving through their enterprises. Eight in 10 orga­nizations' data quality efforts are lagging or problematic. These are among the findings of a new survey of 238 data managers conducted by Unisphere Research, a division of Information Today, Inc., in partnership with Melissa.

Posted October 05, 2021

What types of platforms are most viable for modern data analytics requirements? These days, there are a wide variety of choices avail­able to enterprises, including data lakes, ware­houses, lakehouses, and other options—resident within an on-site data center or accessed via the cloud. The options are boundless. It's a matter of finding the best fit for the business task at hand.

Posted October 05, 2021

Today's data-driven organizations demand capabilities that adapt to the enterprise and open new paths of innovation to business users. Achieving leadership in today's economy requires identifying and preparing for the emerging technologies and methodologies that deliver transformation.

Posted September 27, 2021

One of the challenges of working with Hadoop environments has been maintaining the infrastruc­ture for big data projects. That's where cloud makes things easier and, increas­ingly, has served as the underlying infra­structure platform of choice for Hadoop initiatives. At the same time, not every­thing has moved to the cloud just yet for big data environments. Many IT managers expect to live in a hybrid environment. They are planning for multi-cloud data management to deliver business value and are also still relying on old-school approaches and manual tools to support their data environments.

Posted August 02, 2021

To meet the needs of the digital economy of the 2020s, data architecture has evolved into a dif­ferent animal than it was 10, or even 5, years ago. Most notably, there are three trends that have changed the way enterprises look at and design their data architectures.

Posted August 02, 2021

Data onboarding is a crucial but painstaking process that holds back individual companies and entire industries from reaching their full potential. The last thing a company wants is to lose a client over frustration due to data migration. A new survey of 5,000 managers and executives—many from outside IT departments—conducted by Flatfile has found that more than three-quarters of respondents either "sometimes or often" run into problems onboarding data.

Posted June 10, 2021

We're still at the start of the 2020s, and already, things look very different from the preceding decade. For data executives and profession­als, the years ahead may mean change on a scale never seen before in the IT industry. Promising new technologies—as well as redesigned and repurposed older ones—are reshaping the data center and analytics shops in new and exciting ways. We asked industry leaders for their views on what is enhancing the ability of enterprises to compete on data.

Posted June 10, 2021

The move to next-generation databases is driven by their ability to help companies achieve competitiveness and reach customers faster and more efficiently. These new breeds of systems can be a force for business transformation—whether it is generating new sources of revenue, enhancing customer experience, or producing data-driven insights that improve how organizations interact with customers.

Posted May 26, 2021

If you're looking for proof of the hybrid, multi-platform nature of today's data environments, look no further than many SQL Server sites. Linux—not too long ago seen as a competitive platform to all things Microsoft—has become a platform of choice now supporting many SQL Server environments.

Posted April 29, 2021

Today's data environments are becoming more flexible and portable than their more rigid, siloed predecessors, thanks to emerging approaches. Strategies that are the building blocks of portability, adaptability, and rapid delivery—containers, microservices, DevOps, and DataOps—are transforming the way data is managed.

Posted April 29, 2021

Multi-cloud is changing the way we manage data. It's seen as a way to build a more resilient diversity of services while ensuring a greater degree of independence from a single vendor. At the same time, it takes skill to get everything aligned. In recent years, multi-cloud has become a popular approach, with 93% of enterprises using a multi-cloud strategy, according to the latest Flexera/RightScale survey on cloud adoption. The survey found that respondents use an average of 2.2 public and 2.2 private clouds.

Posted April 02, 2021

Data may be at the heart of all digital engagements, but most enterprises are still behind the curve when it comes to effectively identifying and managing it. That's the takeaway from the latest survey of 419 enterprise executives from BARC, which finds continuing challenges with identifying and surfacing the data assets needed to succeed in today's digital economy.

Posted April 02, 2021

One of the most momentous movements reshaping the data technology space in recent years is the push to real-time capabilities. The ability of systems to read and react to situations as they happen is the most compelling competitive advantage of the digital era.

Posted February 10, 2021

The year 2020 has been extremely eventful on many levels. Time­lines for digital transformation—supported by data analytics—suddenly had to accelerate from 5-year horizons to overnight implementations. Expect more of this continuing velocity in the year ahead, as companies fast-track their plans for initiatives ranging from AI to edge computing. These all require enor­mous volumes of quality data, meaning data managers will be quite busy in the months ahead. DBTA spoke to leaders across the industry to gain their perspec­tive on what to expect.

Posted December 10, 2020

When was the last time you ran across a single-vendor data shop? With the proliferation of multiple database engines for multiple purposes, enterprises now take advantage of a range of database types—not to mention an increasing abundance of cloud services. The difficulty is managing these diverse environments—security, provisioning, and access—in a centralized fashion.

Posted December 10, 2020

Both data warehouses and data lakes offer robust options for ensuring that data is well-managed and prepped for today's analytics requirements. However, the two environments have distinctly different roles, and data managers need to understand how to leverage the strengths of each to make the most of the data feeding into analytics systems.

Posted October 08, 2020

This may be the era of the data-driven enterprise, but only a handful of organizations report they are ready for it. There is a growing volume of "dark data" that remains obscure to IT managers and decision makers. This period unfolding before us will be driven by several technology initiatives, from 5G wireless and IoT to AI.

Posted October 08, 2020

Big data has been around in one form or another for a long time, but lately, due to current events and intensified pressure, there has been greater attention focused on data-driven approaches to manage operations and understand customers. Recognizing that value has shifted to the digital realm, businesses have been looking to technologies that will take them to the next level.

Posted September 11, 2020

Enterprises with forward-looking and well-honed data strategies will be able to navigate, and recover more quickly from, today's turbulent economy than their less data-savvy counterparts. However, even leading tech-forward companies are struggling with ways to employ data resources to better reach their customers and markets.

Posted August 11, 2020

The role of cloud computing in today's enterprises continues to accelerate, fueled by both market pressures to compete more aggressively against digital-savvy competitors and, more recently, by the COVID-19 crisis, which has prompted a massive shift to digital work and consumer engagement. While it's clear that cloud computing has a vital role to play in supporting new and existing applications, it presents difficult choices for data managers.

Posted August 11, 2020

Modernization is driving many of today's enterprise data strategies—and cloud stands out as the primary vehicle for attaining this modernization. However, many enterprises are struggling with data quality issues, as well as integrating cloud-based and on-premise data.

Posted June 10, 2020

This year more than ever before, customers are turning to online transactions in response to decreased physical mobility due to the COVID-19 crisis, employees are working from home, and an uncertain economy is demanding smarter ways to compete. At the root of all these capabilities is data and the ability to analyze and act on data-driven insights. What technologies are coming to the forefront to enhance enterprises' ability to compete on data? We asked a number of leading industry experts and solution providers to describe what they see as the most impactful technologies shaping today's data environments.

Posted June 10, 2020

Even the most ambitious data analytics initiatives tend to get buried by the 80/20 rule—with data analysts or scientists only able to devote 20% of their time to actual business analysis, while the rest is spent simply finding, cleansing, and organizing data. This is unsustainable, as the pressure to deliver insights in a rapid manner is increasing.

Posted May 21, 2020

When it comes to DevOps, developers increasingly recognize databases to be code sets that require ongoing integration and deployment. They are "another code deployment which can and should be managed, tested, automated, and improved with the same robust, reliable methodologies applied to application code," according to the authors of a recent survey of 2,000 developers.

Posted April 08, 2020

DevOps, DataOps, AI, and containers all lead to one important innovation for enterprises seeking to be more data-driven—and that is greater automation. Data-driven enterprises cannot function if data resources and applications are in any way being manually administered, deployed, remediated, or upgraded.

Posted April 08, 2020

Quantum computing continues to captivate imaginations. The technology takes advantage of quantum mechanics to deliver exponentially faster speeds by being able to process an almost infinite amount of parallel compute threads delivered as qubits and quantum gates. As Jim Clarke, director of quantum hardware for Intel Labs, describes it, "by harnessing quantum mechanics, quantum computing systems promise an unprecedented ability to simulate and analyze natural phenomena, significantly accelerating the ability to process information and answer questions that would require prohibitive amounts of time even for today's supercomputers."

Posted March 17, 2020

For years, if not decades, database managers have been struggling with the challenges of providing as much access as possible to corporate informa­tion assets while at the same time protect­ing these crown jewels. All of this work, of course, has had to take place within the confines of relatively tight budget and resource constraints. Now, a new generation of solutions and platforms holds great promise in releasing profes­sionals from the more mundane aspects of their jobs to devote more time to the activities that matter to their businesses. However, even with database automation and cloud resources abundantly available on the market, many database managers still spend inordinate amounts of time on low-level tasks.

Posted February 10, 2020

For data managers, AI and machine learning not only offer new ways of delivering rapid insights to business users but also the promise of improving and adding intel­ligence to their own operations. While many AI and machine learning efforts are still works in progress, the technol­ogies hold the potential to deliver more enhanced analytic capabilities through­out enterprises.

Posted February 10, 2020

Clouds and Autonomous Databases are Poised for Growth

Posted December 01, 2019

As we stand at the start of a new year and on the precipice of a new decade—the 2020s, DBTA reached out to industry leaders for their perspectives on not only what's ahead in the year 2020 but also what they see developing as the next decade unfolds.

Posted December 01, 2019

There is a sea change underway in enterprise architecture. Just a few years ago, enterprise administrators were fearful of the security implications of trusting an outside provider to protect their data assets. Although security is still a cloud concern—one which predominates at the time of cloud migration, and even grows stronger post-implementation—the use of cloud platforms has gained widespread acceptance.

Posted October 31, 2019

The data warehouse and data lake each solve different business problems and impose their own unique challenges.Organizations shouldn't write off data warehouses—as they evolve, they are taking on new roles in digital enterprises. Data lakes may add a great deal of flexibility to an enterprise data strategy, but they are supported by fast-breaking technologies that require constant vigilance.

Posted October 31, 2019

Has the meaning of big data changed? Many agree that data no longer has to be "big" to meet today's evolving requirements. In particular, open source and cloud tools and platforms have brought data-driven sensibilities into organizations that previously did not have such expertise, making big data more accessible.

Posted September 26, 2019

With the emergence of data-intensive activities such AI and the Internet of Things, workloads are getting heavier for data managers. Data managers have seen increases in data volume over the last 3 years and expect this trend to continue. They are also finding it difficult to keep up with this growth. Many DBAs manage more than 10 databases, with some handling hundreds.

Posted August 07, 2019

We've reached the point where hybrid cloud arrangements have become commonplace in enterprises, and with this trend come implications for databases and data management. The rise of both hybrid and multi-cloud platforms means data needs to be managed in new ways, industry experts point out. And, there are lingering questions about which data should go into the cloud, and which should stay on-premise.

Posted August 07, 2019

Eight Trends in Data Analytics

Posted July 17, 2019

Increasingly, people across the spectrum of organized human activity—from business to government—are recognizing the importance of better managing and governing their data assets. "Data is becoming an increasingly critical foundation of the economy and of our lives," said Kevin Lewis, director of strategic offer management for Teradata. "The more this happens, the more important regulation will be, not just for privacy, but also for data quality."

Posted July 17, 2019

Real Time Begins to Dominate Data-Driven Agendas

Posted June 26, 2019

While change has always been a part of the database credo, the growing emphasis on data-driven decision making in today's economy has resulted in a dizzying plethora of technologies and methodologies entering the market. The number and scope of game-changing technologies are too numerous to mention, and one thing is certain: Database management will never be the same. We have identified some of the most promising technology initiatives, based on discussions with and input from data experts from across the industry spectrum, gathering their views on the key technologies—well-known or under the radar—that are worth watching.

Posted June 10, 2019

DBAs and the Expanding Cloud World

Posted April 17, 2019

Cloud computing—and everything that goes with it—is dramatically changing the roles and aspirations of database administrators. No longer do DBAs need to be chained to their databases, wrestling with managing updates, applying security patches, and dealing with capacity issues. Moving to a cloud data environment is steadily shifting DBAs' roles from hands-on database overseers to value-drivers for their businesses—and enabling a range of career advancement opportunities not seen since the dawn of relational databases.

Posted April 11, 2019

Data-driven attributes that businesses are relying on for growth in the digital economy—AI, machine leading, and the Internet of Things—require databases that are robust and flexible. However, many enterprises are encumbered by the licensing and support issues that typically accompany database systems, resulting in potentially high and unexpected costs, as well as skills shortages.

Posted April 09, 2019

Enterprise agility isn't a single initiative but rather a collection of activities and technologies that lead toward that goal. This includes adoption of microservices, containers, and Kubernetes to increase the flexibility of systems, applications, and data by releasing them from underlying hardware. In addition, practices such as DevOps are helping to increase the level of collaboration possible for fast-moving enterprises.

Posted April 09, 2019

Automation Takes on the Heavy Lifting of Data Management

Posted March 06, 2019

Increasingly, cloud services are seen as a vital resource in the data manager's toolkit. There's good reason why cloud is a preferred option: There are simply not enough on-premise resources to keep up with the growth of data management requirements. Organizations keep evolving, business priorities keep shifting, data compliance requirements keep expanding, and user demands keep growing. Already, one-fourth of corporate data is being maintained by cloud providers, and data managers intend to move as much of their data environments into the cloud as soon as they can. 

Posted February 08, 2019

How fast and far can databases grow, and how can such growth be sustained? That's the question faced by many data managers these days, who deal with growing demands from their businesses for real-time, analytical capabilities, incorporating data-driven initiatives such as the Internet of Things and artificial intelligence. They are responding and keeping up with these requirements through a combination of cloud resources and automation.

Posted December 04, 2018

The year just ending has been an interesting one for data managers. Artificial intelligence (AI) and machine learning took center stage, which also meant an increasingly glaring spotlight on data sourcing, management, and viability. The continued rise of the Internet of Things (IoT) also meant no letting up on demands for data environments to deliver requirements fast and furiously. The year ahead will bring more of the same—as well as a continuation of the transformation of information management.

Posted December 04, 2018

There is no shortage of content flowing through today's enterprises, including data, documents, graphics, videos, and more. This is raw material that provides a wealth of opportunities—many of which are untapped—to businesses. The catch is that this data and content is scattered across various systems inside and outside of enterprises. Plus, there is not enough understanding of who views which content, and what is motivating them to consume the content. As more organizations seek to embrace digital transformation, they are turning to content automation as a way to deliver information quickly and effectively to their customers.

Posted October 10, 2018

These days, clouds are everywhere, providing today's database managers with an impressive range of options to choose from—including public cloud, private cloud, and, for most, somewhere in between in the hybrid realm. There may be multiple variations within a single organization, and these distinct hybrid environments are constantly evolving as well. These may be "intentional" and "accidental" hybrid environments, but accidental or not, "variety" is the watchword for many hybrid projects.

Posted October 10, 2018

Everyone wants to be part of a data-driven enterprise, and for good reason. Data analytics, when applied in a meaningful way, provides an enormous competitive advantage. There's a catch to this though that frequently gets overlooked amidst the glowing analyst projections and keynote speeches about a limitless future in which systems and machines do all the heavy lifting and thinking for businesses. Data—the right kind, in the right sequence, in the right context—doesn't just magically drop out of the cloud. It needs to be discovered, identified, transformed, and brought together for analysis, management, and eventual storage.

Posted September 04, 2018

This may seem contradictory at first glance: Fresh data from the database user community finds that data lakes continue to increase within the enterprise space as big data flows get even bigger. Yet, at the same time, enterprises appear to have pulled back on Hadoop implementations.

Posted August 08, 2018

This year is an expansive one for the database ecosystems that have evolved around the major platforms. Artificial intelligence (AI), machine learning, the Internet of Things (IoT), and cloud computing are now mainstream offerings seen within the constellations of database vendors, partners, and integrators.

Posted August 08, 2018

There's a new generation of technologies reshaping data management as we know it. To explore some of the game-changing technologies or approaches that are having the most profound impact on today's enterprises, DBTA asked industry experts and leaders to cite what they see as having the most positive impact. The following are eight areas effecting the most change.

Posted July 02, 2018

The New World for Data Replication in Data-Driven Enterprises

Posted April 26, 2018

The impact of cognitive computing technologies—including artificial intelligence (AI) and machine learning (ML)—is increasingly being felt in data centers and database operations of all sizes, across all industries. Research shows that AI and related cognitive technologies are no longer just experiments conducted by computer or data scientists—they are part of a real-world technology wave that is already showing tangible business results.

Posted April 12, 2018

DevOps Brings the IT Workplace into Greater-Than-Ever Alignment

Posted April 04, 2018

The rise of DevOps, which promises to bring development and operations teams into alignment, is bringing database managers and administrators ever closer to the key touchpoints of their businesses. DevOps seeks to ensure the continuous delivery and consistent cadence of software releases and means that data professionals will have a key role to play in their organizations' information technology strategy. It's not happening a moment too soon—nimble, tech-savvy competitors have learned to leverage data as strategic business assets and are biting ever deeper into just about every existing market.

Posted March 22, 2018

An astounding array of new technologies and approaches have emerged on the database scene over the past few years that promise to turn the next 12 months into a time of unprecedented transformation for the database landscape. There are new developments, along with reinforcement of tried-and-true technologies, some of which may help make the jobs of data managers just a bit easier.

Posted February 01, 2018

Citizen Developers Are Encouraged and Are Delivering Value

Posted February 01, 2018

There are two prevailing views when it comes to blockchain and enterprise data. One is that it's the most secure solution ever to come along. The other is that it is the fad of the moment that puts essential data in the unregulated wilds of the global internet.

Posted January 02, 2018

There never has been a more interesting time to be involved in the data management field. Data not only has become "the new oil" but is also the catalyst that is powering organizations to new heights of success. The past year has seen the rise of powerful analytics and an embrace of new tools and platforms emerging to more effectively tap into the power that data offers. DBTA reached out to industry experts to document the most important trends shaping data management in 2018.

Posted December 01, 2017

The staid relational database has been under attack from all quarters—it's too inflexible, it's too siloed, it's too slow for today's real-time requirements. However, relational databases still power many of the most critical data environments across enterprises—both core legacy systems as well as new-age systems of engagement. In today's enterprises, then, the question becomes: How are new technologies—especially the cloud and NoSQL databases—affecting relational database adoption?

Posted November 01, 2017

Real-time data delivery represents the next frontier of intelligent enterprises, and there is great potential value in the ability to immediately sense and respond to opportunities and threats. At the same time, enterprises are encumbered by existing or legacy technologies and methodologies that may add latency to their data-delivery efforts. What will a real-time enterprise look like?

Posted November 01, 2017

8 Rules of the Road for Fast Data Management and Analytics

Posted August 16, 2017

We're still very much in the early days of artificial intelligence (AI). However, money is pouring into AI initiatives at astounding rates, and enterprises need to move at a deliberate speed to adopt and leverage AI across their systems, applications, and data.

Posted August 09, 2017

It's been long acknowledged that data is the most precious commodity of the 21st-century business, and that all efforts and resources need to be dedicated to the acquisition and care of this resource. Lately, however, executives have become enamored with the vision of transforming their organizations into "data-driven" enterprises, which move forward into the future on data-supported insights. So, what, exactly, does the ideal "data-driven enterprise" look like?

Posted July 05, 2017

DevOps—the close working alliance between development and operations teams—is catching hold in enterprises dependent on continuously and frequently delivering new versions of software, whether for internal consumption or external services.

Posted July 05, 2017

What are the enabling technologies that make enterprise architecture what it is today? There are a range of new-generation technologies and approaches shaping today's data environments. The key is putting them all together to help enterprise architecture fit into the enterprise's vision of itself as a data-driven organization. Tools and technologies emerging within today's data-driven enterprise include cloud, data lakes, real-time analytics, microservices, containers, Spark, Hadoop, and open source trends.

Posted May 15, 2017

Today's enterprise database environments are growing in size and complexity, fueled by rising data volumes and new business demands. Many databases that have been at the heart of existing enterprises to power mission-critical applications are now being positioned to support new Digital Native businesses. As a result, 24x7 high availability is no longer a luxury for select applications; it's a necessity for the bulk of the business—many organizations can no longer afford downtime in their data environments—even for a minute.

Posted April 18, 2017

As mobile has pushed deeper into enterprises, there is a growing recognition that it may be possible to run significant parts of businesses from relatively small devices. While mobile devices may not be ready to run entire enterprises, in many cases, they certainly can run more limited functions.

Posted April 18, 2017

Today's successful organizations are data-driven, and many are building, maintaining, and accessing databases that scale well beyond the terabyte range. In fact, many have total data assets that now measure in the petabytes. But it's not just the size of databases that is expanding.

Posted February 21, 2017

Are enterprises more or less secure than 5 years ago? That's the big question of the moment, especially with ongoing revelations about state-sponsored hacking, as well as an unending stream of reports about customer and employee data being compromised by even the most seemingly security-conscious organizations. Awareness of data security is running at a fever pitch at the highest levels of government and business organizations. There have been plenty of technology advances, and awareness has grown. Still, the wave of breaches and threats never seems to abate, and likely never will.

Posted February 08, 2017

As enterprises accelerate their movement of data into the cloud, a slew of new challenges are presenting themselves on the security front. For users of external or public cloud services, the risks are well understood. However, private and hybrid clouds are not immune to security vulnerabilities either. Thanks to private clouds, data is proliferating across various parts of the enterprise, along with the potential for insider abuse, according to a new Unisphere Research report.

Posted January 03, 2017

The past year was a blockbuster one for those working in the data space. Businesses have wrapped their fates around data analytics in an even tighter embrace as competition intensifies and the drive for greater innovation becomes a top priority. The year ahead promises to get even more interesting, especially for data managers and professionals. Leading experts in the field have witnessed a number of data trends emerge in 2016, and now see new developments coming into view for 2017.

Posted January 03, 2017

Business intelligence (BI) and analytics are at the top of corporate agendas this year, and with good reason. The competitive environment is intense, and business leaders are demanding they have access to greater insights about their customers, markets, and internal operations to make better and faster decisions—often in real time. There have also been dramatic changes with BI and analytics tools and platforms. The three Cs—cloud, consolidation, and collaboration—are elevating BI and analytics to new heights within enterprises and gaining newfound respect at the highest levels.

Posted October 24, 2016

There is a tug-of-war of sorts going on in organizations today. On one hand, there is pressure on IT staff to maintain systems' uptime and availability along with a growing focus on data security, while dealing with the multitude of maintenance-level tasks, such as applying upgrades, fixes, and patches. But on the other hand, there is a growing requirement for IT to support the business as it seeks to use data in new ways for strategic benefit.

Posted October 07, 2016

Big Data Means Big Transformation

Posted October 07, 2016

NoSQL and Hadoop—two foundations of the emerging agile data architecture—have been on the scene for several years now, and, industry observers say, adoption continues to accelerate—especially within mainstream enterprises that weren't necessarily at the cutting edge of technology in the past.

Posted October 04, 2016

Data Integration for the Modern Enterprise - How Cloud Shifts the Balance

Posted September 28, 2016

SHARE recently wrapped up its summer conference in Atlanta. Following the event, Harry Williams, the user group's new president, shared his thoughts on the changes taking place and the goals he is setting for the organization.

Posted September 06, 2016

SHARE recently wrapped up its summer conference in Atlanta. James Vincent, immediate past president of SHARE, reflected on the changes that have taken place in the IT industry during his tenure and the key takeaways from the event which took place July 31-August 5. "One takeaway is that SHARE is on the right track when it comes to its focus on the new IT generation, what we call zNextGen," said Vincent.

Posted August 20, 2016

Can Oracle and its partners keep up with the increasing demands of customers for real-time digital capabilities? Is the Oracle constellation of solutions—from data analytics to enterprise applications—ready for the burgeoning requirements of the Internet of Things (IoT) and data-driven businesses? For Oracle—along with its far-flung network of software vendors, integrators, and partners—times have never been so challenging.

Posted August 04, 2016

Organizations have directed a lot of attention recently to consolidation, automation, and cloud efforts in their data management environments. This will purportedly result in decreased demand for data managers and the need for fewer DBAs per groups of databases. However, the opposite seems to be occurring. In actuality, there is a growing need for more talent, as well as expertise to manage through growing complexity. A new survey, sponsored by Idera and conducted by Unisphere Research among more than 300 data executives, managers, and professionals finds that a more challenging data environment is arising due to a confluence of factors.

Posted July 12, 2016

The data manager now sits in the center of a revolution swirling about enterprises. In today's up-and-down global economy, opportunities and threats are coming in from a number of directions. Business leaders recognize that the key to success in hyper-competitive markets is the ability to leverage data to draw insights that predict and provide prescriptive action to stay ahead of markets and customer preferences. For that, they need to keep up with the latest solutions and approaches in data management. Here are 12 of the key technologies turning heads—or potentially opening enterprise wallets—in today's data centers.

Posted June 09, 2016

Database as a service, also known as DBaaS, offers a solution to some key issues that have vexed enterprise database shops for years. That is, how to maintain and update back-end technologies; how to integrate data from multiple, changeable sources without the need to rewrite the applications that depend on them; and how to make data readily accessible to end users who need it regardless of the device they are using.

Posted April 25, 2016

The need for data integration has never been more intense than it has been recently. The Internet of Things and its muscular sibling, the Industrial Internet of Things, are now being embraced as a way to better understand the status and working order of products, services, partners, and customers. Mobile technology is ubiquitous, pouring in a treasure trove of geolocation and usage data. Analytics has become the only way to compete, and with it comes a need for terabytes—and gigabytes—worth of data. The organization of 2016, in essence, has become a data machine, with an insatiable appetite for all the data that can be ingested.

Posted April 25, 2016

The emerging Internet of Things (IoT) represents a huge opportunity for today's enterprises but also poses risks. Many organizations are challenged to open up their systems to ever-growing networks of devices, sensors, and systems that are relentlessly spewing data that may or may not be of value. But questions about security and systems performance swirl around as well.

Posted March 25, 2016

9 Trends to Watch in the Growing Big Data Market

Posted February 16, 2016

Cloud-borne data is becoming commonplace—at least at the edges of the enterprise. Organizations are relying, both formally and informally, on cloud-based services for supplemental storage, file sharing, and content management. The challenge now is to bring core enterprise data into the cloud, to render data ranging from financials to sales to performance analytics as services.

Posted February 10, 2016

Storage requirements are growing by leaps and bounds, and more organizations are turning to cloud computing to manage the load. However, cloud isn't necessarily seen as the best approach to data storage bursting—rather, it's mainly being used for backup and for hosting development and test environments, according to a new survey.

Posted February 10, 2016

It is often said that the only constant is change. For data executives and professionals, the coming year will only bring a lot more of it. Developments as diverse as cloud, big data, real time, NoSQL, analytics, and the Internet of Things (IoT) will continue to reshape enterprise data operations and opportunities as we know them. Here are 16 trends that will shape the enterprise data landscape in 2016.

Posted December 02, 2015

There's no question that the pace of data movement has quickened dramatically in recent years. This calls for new strategies for integrating data at the speed of business. That is the challenge as companies increasingly rely on data analytics in their decision making. In a new survey, a majority of managers and professionals (57%) state their business leaders now rely heavily on analytics in their day-to-day decision making. The survey, covering 303 data managers and professionals and conducted by Unisphere Research, a division of Information Today, Inc., finds that organizations are employing a range of new strategies and approaches to improve the speed of data delivery and integration. The survey, among members of the Independent Oracle Users Group (IOUG), and sponsored by Oracle, included respondents from organizations of all sizes and across various industries.

Posted December 02, 2015

What does it take to have an always-on organization? While an impressive array of technology exists to deliver data on a real-time, continuous basis, even those organizations with multiple redundancies built into their systems and networks still face challenges keeping up.

Posted October 22, 2015

There's unrelenting pressure on businesses to compete on analytics and to be able to anticipate customer needs and trends ahead of the curve. Enterprises are looking to expand BI and analytics capabilities as far and wide as technologies and budgets will allow them to go. As a result, the continuing advance of analytic capabilities across the enterprise has reached a "tipping point."

Posted October 07, 2015

There are various terms being bandied about that describe the new world data centers are entering—from the "third platform" to the "digital enterprise" to the "always-on" organization. Whatever the terminology, it's clear there is a monumental shift underway. Business and IT leaders alike are rethinking their approaches to technology, rethinking their roles in managing this technology, and, ultimately, rethinking their businesses. The underlying technologies supporting this movement—social, mobile, data analytics, and cloud—are also causing IT leaders to rethink the way in which database systems are being developed and deployed.

Posted September 24, 2015

10 Ways In-Memory Databases are Helping Enterprises Get Ahead

Posted September 24, 2015

The Eight Things That Matter Most in Data Management Now

Posted September 09, 2015

Database Skills More Important Than Ever in Emerging Digital Enterprises

Posted August 19, 2015

With the release of Oracle Cloud Platform 2015 and new Oracle Cloud Platform Services, things are clouding up across the Oracle landscape—but in a positive way. Larry Ellison, chairman and chief technology officer for Oracle, has made it clear in pronouncements that Oracle is in the cloud to stay.

Posted August 18, 2015

Nowadays, data moves well beyond the data center—as well as beyond corporate walls. The challenge is to support data as it moves from data center to cloud, from cloud to cloud, and from cloud to data center. This issue was explored in a recent survey conducted by Unisphere Research among the members of the Independent Oracle Users Group (IOUG).

Posted June 25, 2015

What matters most in data management in 2015? There are a lot of moving parts that data managers and professionals need to attend to in today's enterprises. Databases need to be wide open and accessible to all parts of the business, but at the same time, secure and free of tampering. Unstructured forms of data—such as log data, documents, graphics, video, and social data—need to be prepared and ready for analysis in the same way structured files have been ready for years.

Posted June 25, 2015

The demand for effective data management is intensifying. At the same time, the database market has expanded into a wide array of solutions—from traditional relational database management systems to alternative databases such as NoSQL, NewSQL, cloud, and in-memory offerings.

Posted May 19, 2015

System z revenues - which doubled in the first quarter of 2015 - proved to be one of the few positive line items in IBM's latest spate of downward numbers. Revenues from System z mainframe server products increased 118% compared with the year-ago period. Total delivery of System z computing power, as measured in MIPS (millions of instructions per second), increased 95%.

Posted April 27, 2015

Many DBAs are now tasked with managing multi-vendor environments, and handling a variety of data types. Increasingly, DBAs are turning to strategies such as database automation to be able to concentrate more on the big picture of moving their enterprises forward.

Posted April 23, 2015

SUSE and Veristorm are partnering to provide certified high-performance Hadoop solutions that run directly on Linux on IBM z Systems, IBM Power Systems, and x86-64. Customers with IBM z Systems can team SUSE Linux Enterprise Server for System z with Veristorm zDoop, a commercial distribution of Hadoop supported on mainframes.

Posted April 13, 2015

There are actually many advantages to adopting or subscribing to a cloud-based data services infrastructure. For starters—and this may be the only reason companies need to make the move—there's the simplicity cloud and data as a service can offer. In many ways, cloud and data as a service free enterprises and their data teams from the technical intricacies of deploying systems and solutions.

Posted April 06, 2015

BMC has begun shipping new capabilities in its mainframe management suite, aimed at helping IT executives reduce IBM Monthly License Charge (MLC) software costs. BMC Cost Analyzer is designed to help users better manage their mainframe budget and reduce MLC costs by up to 20% through workload placement, the vendor claims.

Posted March 16, 2015

WANTED: Professionals to Educate and Enlighten Enterprises on Data Security

Posted February 11, 2015

The "Internet of Things" (IoT) is opening up a new world of data interchange between devices, sensors, and applications, enabling businesses to monitor, in real time, the health and performance of products long after they leave the production premises. At the same time, enterprises now have access to valuable data—again, in real time if desired—on how customers are adopting products and services.

Posted February 11, 2015

The 7 Dramatic Shifts Coming to Data Management in 2015

Posted January 29, 2015

8 Steps to Building a Modern Data Architecture

Posted January 08, 2015

Exploding data assets and the need for greater agility are helping to drive the move to virtualization. More than two-thirds of organizations in a recent Unisphere Research survey among members of the Independent Oracle Users Group indicate that the number of Oracle databases they manage is expanding. At the same time, many managers admit that their IT departments are sluggish when it comes to responding to new business requirements. For more than 50% of organizations, it takes their IT department 30 days or more to respond to new initiatives or deploy new solutions. For one-quarter of organizations, it takes 90 days or more.

Posted December 03, 2014

The rise of digital platforms is spurring new innovation and new thinking within the data management world to an unprecedented degree, and it is recasting the look, feel, and functionality of solutions and approaches to data applications. There are many business opportunities arising from digital platforms that call for proactive leadership or engagement by data managers. A prime example is the emergence of the Internet of Things, which SMAC makes possible.

Posted December 03, 2014

The Unfolding Future: More Data, Not Enough Data Gurus

Posted October 08, 2014

Organizations have been collecting data for years, but never before has there been such urgency to have it immediately available. The business need is pressing—decision makers need up-to-the-minute situational awareness in a volatile global economy.

Posted October 08, 2014

In-Memory Databases Speed Up Their Foray into the Enterprise

Posted September 11, 2014

Big data is coming from everywhere and anywhere, creating massive headaches for data managers and IT executives. The good news is that some enterprises are gaining a semblance of control over, and are seeing business value from, their big data assets. What's troubling though is that most organizations are only just beginning to recognize the scope of the challenge that lies ahead of them and are not satisfied with the pace of data integration.

Posted August 05, 2014

Speed and Performance in Oracle's Spotlight This Year

Posted August 05, 2014

This is perhaps the most exciting era the database industry has ever seen. As they face a hypercompetitive global economy, enterprises are reinventing and disrupting themselves at an unprecedented pace—and are embracing data to do so.

Posted June 11, 2014

Backing Up the Data-Driven Enterprise

Posted April 04, 2014

Cloud database technology may be ready for the enterprise, but enterprises are not quite ready for cloud databases. Even leading cloud database proponents agree that cloud databases are a relatively new—and untested phenomenon.

Posted April 04, 2014

Cloud Databases Rise to Meet the Needs of a More Agile and Data-Driven Enterprise

Posted March 12, 2014

The Data Warehouse's New Role in the Big Data Revolution

Posted February 26, 2014

There's no doubt that the management at Target had a miserable holiday season at the end of last year, between all the bad PR that came out about the online theft of 40 million customers' data records—later revised to be even higher—and the costs of providing disclosures and working with banks, and the headaches of potentially expensive lawsuits that are being filed. Such is every organization's nightmare, the price of openness and accessibility. According to a new survey of 322 data and IT managers, there is a growing awareness among enterprise executives and managers about the potential issues to enterprise data security.

Posted February 10, 2014

In order to be effective, big data analytics must present a clear and consistent picture of what's happening in and around the enterprise. Does a new generation of databases and platforms offer the scalability and velocity required for cloud-based, big data-based applications—or will more traditional relational databases come roaring back for all levels of big data challenges?

Posted February 10, 2014

How to Manage the Next Generation of Big Data Solutions

Posted January 20, 2014

NoSQL, NewSQL and Hadoop - Beyond the Hype and Ready for the Enterprise

Posted December 17, 2013

While there have always been many database choices, it's only recently that enterprises have been embarking on new journeys with their data strategies. Today's database landscape is increasingly specialized and best of breed, due to the expanding range of new varieties of databases and platforms—led by NoSQL, NewSQL, and Hadoop. This is complicating the already difficult job of bringing all these data types together into a well-integrated, well-architected environment.

Posted December 04, 2013

How Enterprises Maintain the Engine Behind Data Growth

Posted December 04, 2013

There is no limit to the potential, business- building applications for big data, springing from the capability to provide new, expansive insights never before available to business leaders. However, the new forms of data, along with the speed in which it needs to be processed, requires significant work on the back end, which many organizations may not yet be ready to tackle. IT leaders agree that to make the most of big data, they will need to redouble efforts to consolidate data environments, bring in new solutions, and revisit data retention policies. These are the conclusions of a new survey of 322 data managers and professionals who are members of the Independent Oracle Users Group (IOUG). The survey was underwritten by Oracle Corp. and conducted by Unisphere Research, a division of Information Today, Inc.

Posted September 26, 2013

Oracle holds an enviable position in the IT marketplace with a wide array of database systems, development tools, languages, platforms, enterprise applications, and servers. Riding the coattails of this industry giant is a healthy and far-flung ecosystem of software developers, integrators, consultants, and OEMs. These are the partners that will help make or break Oracle's struggle with new forces disrupting the very foundations of IT. And lately, Oracle—long known for its own brand of xenophobia and disdain for direct competitors—has been making a lot of waves by forging new alliances with old foes. This is opening up potentially lucrative new frontiers for business partners at all levels.

Posted September 11, 2013

Mobile devices—including employee-owned and corporate-provided smartphones and tablets—are rapidly becoming a primary point of access to more than just email and texting. However, the proliferation of mobile application users also presents new challenges to IT departments, as the users demand access to business-critical data and processes, creating security, management, and development challenges

Posted June 13, 2013

These are heady times for data products vendors and their enterprise customers. When business leaders talk about success these days, they often are alluding to a new-found appreciation for their data environments. It can even be said that the tech vendors that are making the biggest difference in today's business world are no longer software companies at all; rather, they are "data" companies, with all that implies. Enterprises are reaching out to vendors for help in navigating through the fast-moving, and often unforgiving, digital realm. The data vendors that are leading their respective markets are those that know how to provide the tools, techniques, and hand-holding needed to manage and sift through gigabytes', terabytes', and petabytes' worth of data to extract tiny but valuable nuggets of information to guide business leaders as to what they should do next.

Posted June 13, 2013

Databases are restricted by reliance on disk-based storage, a technology that has been in place for several decades. Even with the addition of memory caches and solid state drives, the model of relying on repeated access to information storage devices remains a hindrance in capitalizing on today's "big data," according to a new survey of 323 data managers and professionals who are part of the Independent Oracle Users Group (IOUG). The survey was underwritten by SAP Corp. and conducted by Unisphere Research, a division of Information Today, Inc.

Posted March 14, 2013

Data keeps growing, systems and servers keep sprawling, and users keep clamoring for more real-time access. The result of all this frenzy of activity is pressure for faster, more effective data integration that can deliver more expansive views of information, while still maintaining quality and integrity. Enterprise data and IT managers are responding in a variety of ways, looking to initiatives such as enterprise mashups, automation, virtualization, and cloud to pursue new paths to data integration. In the process, they are moving beyond the traditional means of integration they have relied on for years to pull data together.

Posted March 14, 2013

While no one can dispute the importance of enterprise resource planning (ERP) systems to organizational performance and competitiveness, executives in charge of these systems are under intense pressure to stay within or trim budgets. Close to half of the executives in a new survey say they have held off on new upgrades for at least a few years. In the meantime, at least one out of four enterprises either are scaling back or have had to scale back their recent ERP projects due to budget constraints.

Posted December 06, 2012

In the never-ending battle for enterprise data security, industry experts say there has been progress on several fronts, but there is still much work that needs to be done. There is an enormous amount of data that tends to leak out of the secure confines of data centers, creating a range of security issues. "There are many copies of data which have less security and scrutiny than production environments," Joseph Santangelo, principal consultant with Axis Technology, tells DBTA. "The increased reliance on outsourcers and internal contractors leave sensitive data within corporate walls open to misuse or mistakes." Or, as another industry expert describes it, the supply chain often proves to be the greatest vulnerability for data security. "A typical organization has a direct relationship with only 10% of the organizations in its supply chain — the other 90% are suppliers to suppliers," Steve Durbin, global vice president of the Information Security Forum, tells DBTA.

Posted December 06, 2012

Are today's data systems — many of which were built and designed for legacy systems of the past decade — up to the task of moving information to end users at the moment they need it? And is this information timely enough? In many cases, there's a lot of work that still needs to be done before real-time information, drawn from multiple sources, becomes a reality. A new survey of 338 data managers and professionals who are subscribers to Database Trends and Applications reveals that real-time data access is still a distant pipe dream for at least half of the companies represented in the survey. The survey, conducted by Unisphere Research, a division of Information Today, Inc., in partnership with Attunity in March of 2012, finds that close to half of the survey respondents, 48%, report that relevant data within their organizations still take 24 hours or longer to reach decision makers. This suggests that much data is still batch-loaded overnight.

Posted September 11, 2012

In recent years, the networks of developers, integrators, consultants, and manufacturers committed to supporting database systems have morphed from one-on-one partnerships into huge ecosystems in which they have become interdependent on one another, and are subject to cross-winds of trends and shifts that are shaping their networks. Nowhere is this more apparent than the huge ecosystem that has developed around Oracle. With Oracle's never-ending string of acquisitions, new functionality, and widespread adoption by enterprises, trends that shape this ecosystem are certain to have far-reaching effects on the rest of the IT world. Concerns that percolate through the ecosystem reflect — and influence — broad business concerns. New paradigms — from cloud computing to big data to competing on analytics — are taking root within the Oracle ecosystem long before anywhere else.

Posted September 11, 2012

Social media network-based business intelligence represents the next great frontier of data management, promising decision makers vast vistas of new knowledge gleaned from exabytes of data generated by customers, employees, and business partners. Mining data from Facebook, Twitter, blogs, wikis, and internal corporate networks potentially may surface new insights into impending market shifts, patterns in customer sentiment, and competitive intelligence. It's a rich opportunity not lost on today's organizations, a new survey of 711 business and IT managers from across the globe reveals. A majority of respondents are either planning to collect and analyze data from both proprietary and public social media networks, or are doing so already.

Posted June 13, 2012

Companies are scrambling to learn all the various ways they can slice, dice, and mine big data coming in from across the enterprise and across the web. But with the rise of big data — hundreds of terabytes or petabytes of data — comes the challenge of where and how all of this information will be stored. For many organizations, current storage systems — disks, tapes, virtual tapes, clouds, inmemory systems — are not ready for the onslaught, industry experts say. There are new methodologies and technologies coming on the scene that may help address this challenge. But one thing is certain: Whether organizations manage their data in their internal data centers, or in the cloud, a lot more storage is going to be needed. As Jared Rosoff, director of customer engagement with 10gen, puts it: "Big data means we need ‘big storage.'"

Posted June 13, 2012

There's no question that cloud computing is a hot commodity these days. Companies of all types and sizes are embracing cloud computing-both internally and from external service providers - as a way to cost-effectively build new capabilities. With the rapid growth of cloud comes new questions about responsibility within organizations, in terms of how services will be paid for, who has ultimate say over cloud decisions, and how cloud fits into the overall strategic direction of the business.

Posted March 21, 2012

For enterprises grappling with the onslaught of big data, a new platform has emerged from the open source world that promises to provide a cost-effective way to store and process petabytes and petabytes worth of information. Hadoop, an Apache project, is already being eagerly embraced by data managers and technologists as a way to manage and analyze mountains of data streaming in from websites and devices. Running data such as weblogs through traditional platforms such as data warehouses or standard analytical toolsets often cannot be cost-justified, as these solutions tend to have high overhead costs. However, organizations are beginning to recognize that such information ultimately can be of tremendous value to the business. Hadoop packages up such data and makes it digestible.

Posted March 07, 2012

A new survey of 421 data managers and professionals affiliated with the Independent Oracle Users Group (IOUG) members finds that while most companies have well-established data warehouse systems, adoption is still limited within their organizations. Many respondents report a significant surge of data within their data warehouses in recent times, fueled not only by growing volumes of transaction data but unstructured data as well. Now, the challenge is to find ways to extend data analysis capabilities to additional business areas.

Posted December 01, 2011

Until recently, companies were only warming up to the possibilities of cloud computing. Lately, however, for many enterprise-IT decision makers, cloud is hot, hot, hot. The sea change now underway means many companies are quickly moving from "dipping their toes into cloud computing" to a full-fledged immersion, says Thom VanHorn, vice president of marketing for Application Security, Inc. In 2012, expect to see those same companies dive right in. "The move will only accelerate," he tells DBTA.

Posted December 01, 2011

As data grows, the reflex reaction within many organizations is to buy and install more disk storage. Smart approaches are on the horizon but still only prevalent among a minority of companies. How is it data has grown so far so fast? Technology growth along the lines of Moore's Law (doubling every 18 months) has made petabyte-capable hardware and software a reality. And data growth itself appears to be keeping pace with the hardware and systems. In fact, a petabyte's worth of data is almost commonplace, as shown in a new survey conducted by Unisphere Research among members of the Independent Oracle Users Group (IOUG). In "The Petabyte Challenge: 2011 IOUG Database Growth Survey," close to 1 out of 10 respondents report that the total amount of online (disk-resident) data they manage today-taking into account all clones, snapshots, replicas and backups-now tops a petabyte.

Posted September 14, 2011

As companies learn to embrace "big data" - terabytes and gigabytes of bits and bytes, strung across constellations of databases - they face a new challenge: making the data valuable to the business. To accomplish this, data needs to be brought together to give decision makers a more accurate view of the business. "Data is dirty and it's hard work; it requires real skills to understand data semantics and the different types of approaches required for different data problems," Lawrence Fitzpatrick, president of Computech, Inc., tells DBTA. "It's too easy to see data as ‘one thing.' "

Posted September 14, 2011

As the economy shifts to expansion mode, and businesses start hiring again, a familiar challenge is rearing its head. Companies are scrambling to find the talent needed to effectively run, maintain, and expand their technology platforms. This is not a new problem by any means, but this time around, it is taking on a greater urgency, as just about every organization relies on information technology to be competitive and responsive to growth opportunities. A new survey of 376 employers finds a majority depend on the educational sector - universities and colleges - to provide key IT skills, often in conjunction with their own internal training efforts. However, few of the executives and managers hiring out of colleges are entirely satisfied with the readiness of graduates.

Posted July 07, 2011

Is the day of reckoning for big data upon us? To many observers, the growth in data is nothing short of incomprehensible. Data is streaming into, out of, and through enterprises from a dizzying array of sources-transactions, remote devices, partner sites, websites, and nonstop user-generated content. Not only are the data stores resulting from this information driving databases to scale into the terabyte and petabyte range, but they occur in an unfathomable range of formats as well, from traditional structured, relational data to message documents, graphics, videos, and audio files.

Posted June 08, 2011

A new survey of database administrators and managers reveals that a pervasive culture of complacency hampers information security efforts, and as a result of lax practices and oversight, sensitive data is being left vulnerable to tampering and theft. While tools and technologies provide multiple layers of data security both inside and outside the firewall, organizations appear to lack the awareness and will to make security stick. The study, "Data in the Dark: Organizational Disconnect Hampers Information Security," was conducted by Unisphere Research among 761 members of PASS, the Professional Association for SQL Server, in September 2010. The survey was fielded in partnership with Application Security, Inc.

Posted March 09, 2011

The recent public release of thousands of leaked U.S. State Department cables by WikiLeaks continues to shake up governments across the world. The information captured and sent out to the wild is not only an embarrassment to U.S. government officials whose candid assessments of foreign leaders were exposed but also to the fact that that the organization with the tightest and most comprehensive data security technologies, protocols, and policies in the world unknowingly fell victim to a massive data breach. Can private corporations or smaller government agencies with less-stringent security protocols and standards expect to do any better? Securing data is tough enough, and now, with the increase of initiatives such as virtualization and cloud computing, the odds of loss of control and proliferation of sensitive data become even greater.

Posted March 09, 2011

The SHARE conference convenes on February 27th in Anaheim, with an agenda packed with industry initiatives and knowledge-sharing on the latest best practices and technology trends. In this Q&A, SHARE president Janet Sun provides her vision for the IBM users group in the coming years. "We see the mainframe as the center of the enterprise IT universe. If you don't think so, try unplugging it," says Sun. "Our organization focuses on enterprise IT, and that includes the mainframe. Today's SHARE membership continues to strive to leverage advances in information technology, and SHARE is a great place to do that."

Posted February 23, 2011

The year 2010 brought many new challenges and opportunities to data managers' jobs everywhere. Companies, still recovering from a savage recession, increasingly turned to the power of analytics to turn data stores into actionable insights, and hopefully gain an edge over less data-savvy competitors. At the same time, data managers and administrators alike found themselves tasked with managing and maintaining the integrity of rapidly multiplying volumes of data, often presented in a dizzying array of formats and structures. New tools and approaches were sought; and the market churning with promising new offerings embracing virtualization, consolidation and information lifecycle management. Where will this lead in the year ahead? Can we expect an acceleration of these initiatives and more? DBTA looked at new industry research, and spoke with leading experts in the data management space, to identify the top trends for 2011.

Posted November 30, 2010

These days, many companies recognize that there are severe repercussions to ignoring or undervaluing data security, and a sizable segment of organizations-at least one-third in many cases-have been taking additional measures to bolster their data security.

Posted November 30, 2010

Many organizations now have, in their possession, the sophisticated analysis tools and dashboards that connect to back-end systems and enable them to peer deeply into their businesses to assess progress on all fronts-from revenues to stock outs to employee performance. However, a recent survey of 279 Oracle applications managers reveals that when it comes to decision making, simple spreadsheets still remain the tool of choice. And business users still wait days, weeks, and months for their IT departments to deliver reports, despite significant investments in performance management systems.

Posted September 07, 2010

Oracle is a fast-changing company, and in recent years, its pace has accelerated to blinding speed. The software giant has expanded well beyond its relational database roots to encompass applications, management tools, service-oriented architecture and middleware, and even hardware. There are now many components to Oracle - from three major databases, to enterprise resource applications, to web applications to development languages to open source desktop tools.

Posted September 07, 2010

In the midst of turbulent times, many successful businesses learned an important lesson: The closer IT works with the business, the better an organization can weather the storms that blow in. Thus, many savvy companies understand that the managers and professionals who oversee information technology and applications need to be well incentivized to stay on. At the same time, these professionals understand the need to develop expertise in business management and communications. Many companies are looking to information technology to provide an additional competitive edge, and see their Oracle enterprise systems as the cornerstone of this strategy. As a result, a survey finds that Oracle enterprise application managers and professionals appear to have weathered the economic storm. The survey, conducted among 334 members of the Oracle Applications Users Group (OAUG) by Unisphere Research, and sponsored by Motion International, finds an increase in the number of Oracle technology professionals who are near or surpassing the $100,000 mark in their base salaries.

Posted June 07, 2010

In only a few years' time, the world of data management has been altered dramatically, and this is a change that is still running its course. No longer are databases run in back rooms by administrators worrying about rows and columns. Now, actionable information is sought by decision makers at all levels of the enterprise, and the custodians of this data need to work closely with the business.That's because, in the wake of the recent financial crisis and economic downturn, there's a push from both high-level corporate management and regulators to achieve greater understanding and greater transparency across the enterprise, Jeanne Harris, executive research fellow and a senior executive at the Accenture Institute for High Performance, and co-author, along with Tom Davenport, of Competing on Analytics and Analytics at Work, tells DBTA. "In many ways, I think the ultimate result of the financial crisis is that executives realized they cannot delegate analytics to subordinates; they can't view it as technology or math that doesn't really affect them."

Posted June 07, 2010

For many organizations, application information lifecycle management, or ILM, now offers expedient - and badly needed - measures for properly defining, managing, and storing data. Many enterprises are being stymied by a massive proliferation of data in their databases and applications. Growing volumes of transaction data are being digitally captured and stored, along with unstructured forms of data files such as email, video, and graphics. Adding to this tsunami are multiple copies of all this data being stored throughout organizations. At the same time, increasingly tight mandates and regulations put the onus on organizations to maintain this data and keep it available for years to come. Much of this data still resides on legacy systems, which are costly to operate and maintain.

Posted March 04, 2010

An overwhelming challenge - expanding volumes of data - threatens to gum up any productivity improvements seen to date as a result of information technology deployments. All that data is coming in from systems, sensors, and storage area networks, pressuring organizations to expand database inventories, while grappling with associated licensing and hardware costs. Plus, many compliance mandates demand that this data be stored for long periods of time, but remain accessible to auditors and business end users.

Posted March 04, 2010

Corporate management is complacent about data security. Efforts to address data security are still ad hoc, and not part of an overall database security strategy or plan. Companies are not keeping up with the need to monitor for potential risks. More monitoring tends to be ad hoc or on-the-fly, versus more organized or automated systematic approaches. These are the findings from new research from Unisphere Research and the Independent Oracle Users Group (IOUG), which shows that the recent economic downturn has taken a toll on data security efforts within enterprises.

Posted December 14, 2009

As we enter the next decade of the millennium, we will see information technology becoming more ubiquitous, driving an even greater share of business decisionmaking and operations. IT has proven its muster through the recent downturn as both a tactical and strategic weapon for streamlining, as well as maintaining competitive edge. Now, as we begin the next round of economic recovery, companies will be relying on IT even more to better understand and serve their markets and customers. Yet, there are many challenges with managing a growing array of IT hardware, software, and services. To address these requirements, businesses continue to look to approaches such as analytics, virtualization, and cloud computing. To capture the trends shaping the year ahead, Database Trends and Applications spoke to a range of industry leaders and experts.

Posted December 14, 2009

This year, despite a turbulent economy marked by painful layoffs in many sectors, database professionals appear to be weathering the storm. In fact, database professionals reported higher incomes and bonuses this year over last. Still, a sizeable segment of professionals saw changes in their jobs as a result of economic conditions, and many are concerned going forward about the impact of tighter budgets on their departments' performance.

Posted September 14, 2009

Why do business decision makers need to wait for IT to deliver performance reports on the business? Why can't they build their own reports, and gain rapid access to answer the questions they have?

Posted September 14, 2009

This is a time of great change for data centers. Technology is advancing and getting smarter, and workloads and performance demands keep growing. For this issue of Database Trends and Applications, we sought a range of industry views on the most profound—and perhaps unexpected—changes reshaping data centers and enterprise it.

Posted June 15, 2009

In today's competitive and crisis-ridden market, companies are under pressure to rapidly deliver results and make necessary changes—which requires that decision makers have accurate and timely information readily available. However, many executives have doubts about the timeliness of the information they now receive through their current BI and analytics systems.

Posted June 15, 2009

Business intelligence (BI) and analytics solutions have been available for years now, and companies have learned to employ these tools for a variety of purposes, from simple report generation and delivery to more sophisticated data integration, executive dashboards, and data mining. They also recognize the need to get beyond spreadsheets, and to be able to provide more sophisticated, pervasive, and automated BI solutions to more end-user decision makers. However, most see their efforts stymied by the historically high cost of BI software and the complexity of available solutions.

Posted March 15, 2009

Many IT and business managers are now familiar with the concept of virtualization, especially as it pertains to the ability to run a secondary operating system within the same hardware that already supports a separate OS brand. Seasoned data center professionals have been aware of virtualization as a capability available on mainframes for years. The ability of virtualization to provide advantages to data center operations in terms of systems consolidation and simplifying administration has been well-documented.

Posted March 15, 2009

More than a decade ago, some IBM researchers began pitching a bold vision of information technology, called utility computing at the time, in which processing power would be made available just as electricity is available, as easily accessible as plugging into an outlet in a wall.

Posted January 15, 2009

Even the best economists can't agree on what the business landscape will look like in the year ahead, but IT industry leaders agree that enterprises are likely to be more cautious than ever in how they spend their IT dollars (or euros, pounds, or rupees). Most also agree that any downturn that may be looming won't be a repeat of 2001, when IT departments were ravaged.

Posted December 15, 2008

The old maxim, "may you live in interesting times" certainly holds true for IT managers and professionals these days. The year 2008 was full of changes and challenges, and 2009 promises even more.

Posted December 15, 2008

Posted November 15, 2008

Posted September 15, 2008

Now more than ever, data has evolved into an asset more strategic and valuable than any raw material or capital construction project. Companies are scrambling to "compete on analytics," recognizing that the one to most effectively leverage information coming out of their systems gets the greatest competitive advantage.

Posted September 15, 2008

An entire industry has sprung up in response to the never-ending battle against complexity, server sprawl, and rising power consumption. Virtualization is now the mantra for beleaguered data center managers looking for ways to consolidate, better utilize, or abstract away their farms of physical servers and hardware. However, in many cases, virtualization itself can lead to even more complexity andoffer uncertain value to the business. Many businesses are finding that virtualization is not ready for core mission-critical applications.

Posted June 15, 2008

Despite efforts to "democratize" business intelligence, it has remained stubbornly confined to a chosen few within organizations. Although vendors have worked hard to convince enterprises that their BI solutions could be extended to line-of-business managers and employees, high-end analytic tools have remained confined to power users or analysts with statistical skills, while the remainder of the organization relies on spreadsheets to cobble together limited pieces of information.This disconnect was confirmed in a 2007 survey conducted by Unisphere Research for the Oracle Applications Users Group, which found that most companies are still a long way off from the ideal of BI for all. The OAUG survey found that for the most part, BI reporting remains tied up in IT departments, and is still limited to analysts or certain decision makers. The majority of survey respondents said that it takes more than three to five days to get a report out of IT. Overall, the survey found, fewer than 10 percent of employees have access to BI and corporate per­formance management tools.

Posted March 15, 2008

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