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
Protecting Against Cryptomining Malware in 2019: A Layered Approach to Device Management and Security
Posted August 07, 2019
Earlier this year, Google became the first major tech giant to be hit with a General Data Protection Regulation (GDPR) fine—approximately $56.8 million. The stated reason: not giving users enough information about consent policies and sufficient control over how their personal data was being used. However, according to a recent report, 86% of businesses use live customer data for application testing because testers believe this provides the most realistic assessment of how an application will perform "in the wild" for real people. This poses significant risk to organizations.
Posted July 18, 2019
The Right and Left Brain of DevOps and Security: How to Gain a Meeting of the Minds Instead of a Battle of Wills
Posted July 18, 2019
The Perils of Ignoring Employee ‘Leaver' Data in Regulated Industries
Posted July 18, 2019
DBTA 100 2019 - The Companies That Matter Most in Data
Posted June 12, 2019
AI, machine learning, and predictive analytics are used synonymously by even the most data-intensive organizations, but there are subtle, yet important, differences between them. Machine learning is a type of AI that enables machines to process data and learn on their own, without constant human supervision. Predictive analytics uses collected data to predict future outcomes based on historical data.
Posted June 10, 2019
With deep learning so much praised, you've probably read a lot about its positive side. Let's skip the positives and instead concentrate on the things that can go wrong with deep learning-based demand forecasts as well as offer some ways to overcome these problems.
Posted June 10, 2019
Meet the Data Privacy Challenge: Creating a Culture of Responsibility
Posted June 10, 2019
Information Governance and Data Management Initiatives: Are You Still Waiting to See What the Future Brings?
Posted June 10, 2019
Quantum computing will bring unprecedented advances in medicine, science, and mathematics—knowledge currently out of reach. Many secrets of the universe are on the verge of discovery. But, are we ready for everything to be unlocked? Are we prepared to manage what comes with quantum computing's limitless architecture?
Posted June 10, 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
Web data is the world's largest untapped source of data. And now, web data in large volumes can be captured quickly, efficiently and cost-effectively with the introduction of web data integration, a practice that identifies, extracts, prepares, and integrates data for consumption by business applications, analytics, and processes.
Posted June 10, 2019
When it comes to cloud technology, more and more businesses are realizing the benefits that cloud can provide them and are beginning to seek more cloud computing options to conduct their business activities. And obviously, Amazon, Microsoft, Google, Alibaba, IBM, and Oracle plan to capture this spend by providing a dizzying array of IaaS and PaaS offerings to help enterprises build and run their services.
Posted May 01, 2019
Data pipelines speed IoT, predictive analytics, and machine learning projects to their final destination. The new generation of data pipelines also supports governance, which is sure to be in the spotlight during 2019. Enterprises will need to be much more stringent about their data usage and lineage, based on new regulations such as GDPR and consumers' higher expectations of security and privacy.
Posted May 01, 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
Many companies and government organizations have jumped on the data bandwagon and are hoping to analyze as much data as possible to discover something that might give them a competitive edge or change their operations. Instead of big insights, they have petabytes of big data. They've become compulsive data hoarders while struggling to develop an actionable plan for that data.
Posted April 09, 2019
There's not a business out there that wouldn't want to defend itself against fraudulent activities, hacking attempts, and operations disruptions. And with cases of fraud and cyberattacks on the rise—$16 billion was stolen from 15.4 million U.S. consumers in 2017—businesses need to pay attention to solutions that can help them identify this kind of behavior. Here's where anomaly detection comes in.
Posted April 09, 2019
How Machine Learning is Changing the Way We Think
Posted April 09, 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
19 Startups to Watch 2019
Posted April 01, 2019
COLLABORATE 2019 is Coming to Texas April 7-11
Posted March 12, 2019
Every day, more technology surrounds us. Things that were once fiction, are now everyday occurrences. None of this is by accident or happenstance, this is only through the work of many professionals and even amateurs in the fields of engineering, electronics, and computer science.
Posted March 12, 2019
From April 7-11th, Oracle users from across the world will gather in San Antonio for the largest user-led, user-focused event where they'll get the real story about Oracle products and experience in-depth education and networking to take their Oracle product impact to the next level.
Posted March 12, 2019
One week is all you need. One week at COLLABORATE 19: Technology and Applications Forum for the Oracle Community equips Oracle users with expertise and insight to accelerate performance and maximize Oracle investments. At COLLABORATE 19, April 7-11 in San Antonio, Texas, the OAUG delivers expert on-prem Oracle Applications knowledge and the latest guidance for the Cloud so users can innovate with their current Oracle solutions and strategically plan for the future. Users share lessons learned from real-life implementations, and solutions providers offer a look at the latest, greatest new products.
Posted March 12, 2019
Competitive business strategy increasingly relies on data analytics. The core techniques of data analysis are increasingly accessible thanks to commodity Business Intelligence packages, modern open source AI tools, and cloud services. Given this level playing field for software and algorithms, competitive advantage typically lies in the unique data that a business can gather and feed into its analytics pipelines.
Posted March 04, 2019
In recent years, an unprecedented numbers of companies have moved to the cloud, which is a trend that shows no sign of slowing. Most companies have moved at least part of their data holdings to the cloud, and many more will follow suit in the next few years, effectively shifting data's center-of-gravity from the data center to the cloud. Many are also leveraging multiple vendors, such as Amazon and Microsoft, as part of a multi-cloud strategy that leverages the best features of multiple offerings. Unfortunately, many of the gains realized by cloud technologies will be lost to downtime during the migration.
Posted March 04, 2019
The flexibility, agility and ultimate cost of machine learning projects can be significantly impacted by data logistics and dependencies, according to Jim Scott, VP, Enterprise Architecture, at MapR. By improving how they pursue machine learning, Scott contends, organizations can attain benefits in both long-term costs and maintenance.
Posted March 04, 2019
At the Cloud Economic Summit in San Francisco, a new consortium called the FinOps Foundation was announced to share best practices for managing the cost of cloud computing. According to the foundation, cloud spending is now a material amount of total IT spend. Similar to the way DevOps ushered in a new way of thinking about development and operations, the foundation says, the FinOps operating model is a combination of systems, best practices, and culture that aims to bring financial accountability to the variable spend model of cloud.
Posted March 04, 2019
In a post-GDPR world, the attention rests on which companies will be impacted by data breaches, what the total fines will be, and what the public scrutiny will entail. Though the impact of the fines—4% of a company's annual worldwide revenue or €20 million ($22.9 million) (whichever is greater)—is certainly eye-catching, a data breach could leave a company destabilized for years afterwards.
Posted February 08, 2019
In the days of cloud computing and agile development, it might seem that being a DBA is somewhat less appealing as a career choice. However, the role of DBA is changing; it is not going away. In fact, it is becoming even more important.
Posted February 08, 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
The past year brought many data breaches and incidents of PII mishandling. With confidential information being compromised routinely, data privacy regulations are also on the rise. Here, top IT executives reflect on the current data security landscape and what we can expect in 2019.
Posted January 02, 2019
Although Windows and Linux were traditionally viewed as competitors, modern IT advancements have ensured much needed network availability between these ecosystems for redundancy, fault tolerance, and competitive advantage.
Posted January 02, 2019
It is the combination of Docker and Kubernetes that is creating a tipping point that will accelerate the industry toward a serverless world capable of powering business agility, lowering administration and management, and disrupting costs.
Posted January 02, 2019
In nearly every industry today, organizations are challenged with finding efficient, secure methods to manage and share data related to transactions, contracts, assets and more. From finance and real estate to healthcare and retail, information silos and disparate databases create operational inefficiencies and make true collaboration between business parties difficult to achieve. However, a new technology has emerged that allows companies to break down these data silos and digitally connect multiple systems, partners and customers: Blockchain.
Posted January 02, 2019
Big data continues to be top of mind while new technologies are also emerging to reel in and uncover important insights. In 2018, a variety of solutions came to the fore and 2019 is setting the stage for another data explosion. Here, several experts in the big data space offer their predictions for what's ahead in 2019.
Posted January 02, 2019
Trend-Setting Products in Data and Information Management for 2019
Posted December 05, 2018
Increasingly, DBAs are seeing artificial intelligence (AI), and machine learning applied to database management and optimization, taking self-healing and self-tuning to the next level. These solutions, from both database and third-party vendors, allow DBAs to spend less time searching for bottlenecks, and more time doing more productive and creative work in support of strategic business goals.
Posted December 04, 2018
Everything changes—especially when we seek to automate tasks. Automation is leading to amazing consumer benefits—from vehicles to clothing to voice-activated devices—and making our lives better. In the workplace, as automation becomes applied to repetitive tasks that are being handled manually, people become concerned about their livelihoods. Will they lose their jobs? How will they provide for themselves and their family? How will automation impact them personally?
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
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
In this new world where data is the coin of the realm, the winners will be enterprises who can quickly and effectively harness data—the right data—to reduce risk, improve business outcomes, and create new value for their customers, employees and other stakeholders. As they work to realize this goal, enterprises are increasingly finding that activating copy, backup, archived and other data located on secondary storage can be just as, if not more, useful for driving digital transformation as the production and original data located on their primary storage.
Posted November 01, 2018
While AI and machine learning cannot—yet—turn back time, cognitive technologies can analyze data in ways that were previously unattainable. Manual modeling on past failure patterns executed by "data scientists" is nothing new, but data analysis performed by AI-powered platforms builds cognitive learning which not only can learn from past failure patterns but more importantly learn to detect issues not known or seen before.
Posted November 01, 2018
There's no easy answer to the dilemma of infrastructure decline. But the obvious response, to attack the problems in piecemeal fashion, clearly doesn't work. That's what organizations have been doing all along: bringing in faster processors, adding databases, deploying more clouds. These may offer temporary relief, but eventually they'll just add to data complexity and congestion.
Posted November 01, 2018
There's a renaissance happening in organizations today. Process automation is now ‘in vogue' again. It's no doubt that robotic process intelligence and artificial intelligence are driving this renaissance, helping to transform the enterprise. But what that transformation looks like is another question entirely.
Posted October 10, 2018
Data lakes have helped organizations deal with the massive amounts of data generated daily. They are intended to serve as a central repository for raw data, a treasure trove for data scientists to analyze and gain actionable insight. They also serve as the foundation for many "self-service" analytics initiatives. While getting data into a lake is simple, getting insight and value from all of that data, however, has proven to be challenging for many organizations. A recent Forrester report found that 60%-73% of all enterprise data goes unused for analytics. This statistic exposes some of the harsh realities of data lakes.
Posted October 10, 2018
Shortly after contracting with a cloud service provider, a bill arrives that causes sticker shock. There are unexpected and seemingly excessive charges, and those responsible seem unable to explain how this could have happened. The situation is urgent because the amount threatens to bust the IT budget unless cost-saving changes are made immediately. But this cloud services sticker shock is often caused by mission-critical database applications, as these tend to be the most costly for a variety of reasons.
Posted October 10, 2018
To stay competitive in today's digitally driven market, the modern enterprise must keep pace with end users' expectations. Customers and employees alike want access to information anytime, anywhere, giving them the flexibility to work, shop, bank, and live on their own terms. While most forward-looking organizations are making strides to deliver this remote access—largely by moving to a hybrid IT model—many are still limited by the state of their back-end infrastructures.
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