Big Data Quarterly Articles



We live in a new world today, with unique challenges heretofore unseen in information technology. To remain at the expected technological apex, organizations should ask themselves these questions.

Posted March 26, 2018

Many organizations nowadays are struggling with the quality of their data. Data quality (DQ) problems can arise in various ways. Common causes of bad data quality include multiple data sources; limited computing resources: Lack of sufficient computing resources; changing data needs; and different processes using and updating the same data.

Posted March 26, 2018

In the IoT world, devices are moving from smart to intelligent due to the advent of artificial intelligence and machine learning. However, this is now hindered due to the natural limitations of the cloud. In order to progress, devices need lower latency, a higher level of independence, and better connectivity.

Posted March 26, 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

Does this sound familiar? You have a backlog of apps that your workforce is craving, and you simply don't have the team (or the time) to build them. In fact, the demand for apps is growing five times faster than IT's capacity to deliver them. This crunch is probably all too familiar for many, and it's forcing IT teams to find new ways to accelerate app development. The age-old question is, do you build, do you buy, or do you do something in between?

Posted March 13, 2018

Big data can help drive decisions in almost every aspect of our lives—from the way financial products are underwritten, learning programs are designed, energy is used, healthcare diagnoses are made, insurance rates are assessed, commerce is conducted, and fraud is prevented—the list is infinite. As these decisions can affect individuals and society as a whole, it is compulsory that data experts apply integrity, transparency, and due diligence into the analytics that mine information and the algorithms that inform our decision making and problem solving.

Posted March 13, 2018

With data lakes being so new to organizations, an early failure can significantly set back the opportunity to fundamentally transform analytics. However, while the potential for big data innovation is significant, organizations are mired with slow, manual, and time-consuming processes for managing the tasks that turn raw big data into relevant business assets and insights. Without addressing these challenges in a systematic way, organizations find that data lake projects turn into labor-intensive, complex endeavors.

Posted March 08, 2018

Websites and the servers that host them are vulnerable to attack, and so too are the networks that are connected to them. Security holes in sites created by human error or application vulnerabilities are a source of trouble for the entire enterprise.

Posted March 08, 2018

Graph databases are increasingly popular. In fact, according to DB-Engines graphs are the fastest growing of any database category since 2013. This growth is fueled in part because many organizations are realizing the value of understanding connections in their data. For companies looking to use a graph database to build behavior and decision-making applications based on real-time evaluation of connected data, there are several key attributes, including integrity, performance, efficiency and scalability.

Posted March 07, 2018

The Changing Role of the Modern DBA: Cloud, NoSQL, and Automation

Posted March 05, 2018

Private equity firm Parallax Capital Partners acquired erwin Data Modeler software from CA Technologies in April 2016. Since then, operating as erwin, Inc. and led by IT industry veteran Adam Famularo, the company has rebranded itself as "the data governance company," launched new products, and made a number of strategic acquisitions—including most recently Rome-based A&P Consulting. Famularo spoke with BDQ about the changes at erwin over the past 2 years and shared his views on where the IT market overall is headed.

Posted February 28, 2018

Good News: Your Database is About to be Autonomous!

Posted February 21, 2018

Qubole, the cloud big data-as-a-service company, is teaming up with Snowflake Computing, a data warehouse built for the cloud, enabling organizations to use Apache Spark in Qubole with data stored in Snowflake. With the new integration between cloud services, data teams are able to build, train, and put in production machine learning (ML) and artificial intelligence (AI) models in Spark using information stored in Snowflake.

Posted February 14, 2018

CloudJumper, provider of a workspace as a service platform for agile business IT, has acquired privately held IndependenceIT (IIT), a provider of WaaS enablement software for automating the deployment of applications, data, and complete workspaces in the cloud.

Posted February 13, 2018

The Changing Role of the Modern DBA in a Big Data World

Posted February 05, 2018

MongoDB 3.6 is now Generally Available (GA), and ready for production deployment. In this short blog series, I'll be taking you on a whirlwind tour of what's new in this latest release:

Posted January 31, 2018

The Changing Role of the Modern DBA - New Skills for Security

Posted January 22, 2018

Cybersecurity and terms written about it, such as "ransomware," "malware," and "hacker" have become part of our regular vocabulary. Concerns about protecting our identities and personal data are on the rise in our day-to-day lives. With the onslaught of news reports about data breaches and various hacks, the awareness is more elevated now than it has been in the past few years.

Posted January 11, 2018

Emerging technologies are outpacing data governance at a rapid clip. Specifically, the rate of growth and development of emerging technologies in areas such as artificial intelligence (AI), the Internet of Things (IoT), and machine learning (ML) drastically exceeds the current speed and willingness of businesses to change their governance models to manage and protect their data and information assets. Unfortunately, the larger the delta becomes between the advancements in technology and the changes in governance, the greater the risks and losses for the business.

Posted January 09, 2018

As the use of cloud expands as a database platform and automated capabilities increase, there are new opportunities for DBAs to move beyond operations and emergency fire-fighting and instead get involved in more innovative, high-level tasks that bring additional value to their organizations. Experts weigh in on what's ahead.

Posted January 08, 2018

A lot has been written about why IoT is going to be absolutely essential to your company. If you are convinced as to the why but wonder about the how, pay attention. Based on all the lessons learned from my engagements around the globe, I am going to tell you how. It basically comes down to three basic phases: preparation, the "real stuff," and embedding it in the organization.

Posted January 08, 2018

In a world where new technologies are often presented to the industry as rainbows and unicorns, there is always someone in a cubicle trying to figure out how to solve business problems and just make these great new technologies work together. The truth is that all of these technologies take time to learn, and it also takes time to identify the problems that can be solved by each of them.

Posted January 05, 2018

As Paul Graham, founder of Y-Combinator, has put it: "Hacking and painting have a lot in common … [hackers and painters] they're both makers." And as modern-day artists, developers will help create the future of cognitive computing and AI. New technology has granted them more paints and more materials with which to paint and sculpt. It will allow them to create works of art never previously envisioned, that are powered by big datasets and cognitive systems. But they can't go it alone. Even da Vinci had his patrons. That leads to the next logical questions. How should organizations support their developers right now? And where should they place resources to ensure their developers reap the greatest benefits from cognitive technologies?

Posted January 04, 2018

The suddenness of the non-relational "breakout" created a lot of noise and confusion and—at least initially—an explosion of new database systems. However, the database landscape is settling down, and in the past few years, the biggest meta trend in database management has been a reduction in the number of leading vendors and consolidation of core technologies. Additionally, we're starting to see database as a service (DBaaS) offerings become increasingly credible alternatives to on-premise or do-it-yourself cloud database configuration.

Posted January 03, 2018

A New Age: AI and Machine Learning Meet the Cloud

Posted January 03, 2018

GDPR Crosses the Pond

Posted January 02, 2018

With cyberattacks on the rise and the EU's new General Data Protection Regulation (GDPR) going into effect in 2018, there is a greater focus on data security and governance. Here six top IT leaders reflect on the changes taking place and offer their predictions for data security and compliance in 2018.

Posted December 13, 2017

Using Web Scraping as a Data Science Tool

Posted December 04, 2017

Databricks, provider of a Unified Analytics Platform and founded by the team who created Apache Spark, has become a partner with Microsoft to expand the reach of its Unified Analytics Platform and address customer demand for Spark on Microsoft Azure.

Posted November 29, 2017

Getting Ready for GDPR

Posted November 28, 2017

Cyberattack—How to Prepare and What to Do If It Happens

Posted November 28, 2017

Moving Beyond Relational With Data Integration

Posted November 28, 2017

No longer the stuff of science fiction, the business uses for cognitive computing, artificial intelligence, and machine learning today include fields as diverse as medicine, marketing, defense, energy, and agriculture. Enabling these applications is the vast amount of data that companies are collecting from machine sensors, instruments, and websites and the ability to support smarter solutions with faster data processing.

Posted November 13, 2017

AtScale is releasing a universal semantic platform for business intelligence (BI) with Microsoft Azure HDInsight, providing enterprises with faster time to insight. AtScale's new offer helps enhance Azure HDInsight customers' ability to quickly turn their Big Data lake into a highly available and performant analytical database.

Posted November 02, 2017

There's a surprising trick for greatly increasing the chances of real impact, true success with many types of machine learning systems, and that is "do the logistics correctly and efficiently."   That sounds like simple advice - it is - but the impact can be enormous. If the logistics are not handled well, machine learning projects generally fail to deliver practical value. In fact, they may fail to deliver at all. But carrying out this advice may not seem simple at all.

Posted October 26, 2017

After years of ambiguous expectations about data governance, organizations now have a better handle on how these programs can help them manage the exponential growth of the data they generate. More importantly, there is an understanding about how the integration, organization, and alignment of that data can help meet or exceed business and technology goals.

Posted October 18, 2017

As companies grow increasingly data-centric in their decision making, product and services development, and their overall understanding of the world they work in, speed and agility are becoming critical capabilities. A common theme in big data and analytics today is "Industry 4.0," representing a new wave of technology that enables the automation necessary for scaling. There's compelling justification for this as companies seek to unlock business value from big data with two broad approaches: the democratization of data with greater access by more users, and the enablement of automation everywhere possible.

Posted September 20, 2017

Big Data and Analytics Becomes Smarter and More Connected

Posted September 20, 2017

Over the last few years, organizations have shifted from using virtual data centers to creating private or hybrid IaaS clouds that allow authorized users to perform self-service provisioning of virtual machines. These environments have reduced administrative workloads, improved the user experience, and discouraged shadow IT, but they have also brought their own challenges. As virtualized environments increase in scale, management techniques have often become far less effective, making it difficult to keep track of virtual machines, their owners, and why the virtual machines were created in the first place.

Posted September 20, 2017

Companies today are spreading their applications across multiple clouds in a hybrid fashion. According to a recent IDC CloudView study among 6,000 IT and line-of-business executives whose organizations have adopted cloud technologies, 73% are implementing a hybrid strategy, which most defined as utilizing more than one public cloud in addition to dedicated assets.

Posted September 20, 2017

Many people are unsure of the differences between deep learning, machine learning, and artificial intelligence. Generally speaking, and with minimal debate, it is reasonably well-accepted that artificial intelligence can most easily be categorized as that which we have not yet figured out how to solve, while machine learning is a practical application with the know-how to solve problems, such as with anomaly detectio

Posted September 20, 2017

When it comes to visualizing data, there is no shortage of charts and graphs to choose from. From traditional graphs to innovative hand-coded visualizations, there is a continuum of visualizations ready to translate data from numbers into meaning using shapes, colors, and other visual cues. However, each visualization type is intended to show different types of data in specific ways to best represent its insight. Let's look at five of the most common visualization types to help you choose the right chart for your da

Posted September 20, 2017

Businesses of all sizes across all industries are rapidly adopting digital transformation models that put data at the center of driving the business forward—as they should. However, putting data at the center of everything the business does can be risky without proper planning and rigorous management. Many companies have been wise to introduce data governance programs to protect corporate data assets and establish a framework for operational excellence when it comes to data management and use. Data governance emphasizes the enforcement of defined standards or policies and provides mechanisms for consistency and repeatable processes, but it is not enough to protect businesses in today's world of data.

Posted September 20, 2017

Nowadays, many firms are already using big data and analytics to manage and optimize their customer relationships. Both technologies can also prove beneficial to leverage a firm's other key assets: its employees! Various HR analytics (also called workforce analytics) examples can be thought of.

Posted September 20, 2017

While Vic Damone and Jane Powell wanted their eggs with a kiss in the 1950s musical Rich, Young and Pretty, in the near future, your kitchen might well know exactly how you want them thanks to the Internet of Things (IoT).

Posted September 20, 2017

Tic toc, tic toc—back and forth swings the privacy pendulum. While we in the U.S. continue to regress on issues of data privacy, the European Union (EU) is proceeding with bold steps to protect the privacy of its citizens. On May 25, 2018, the General Data Protection Regulation (GDPR) becomes the law of the land in the EU. It applies to any company that processes or holds data on EU residents, regardless of where it is located in the world. Popular applications such as Facebook, Twitter, and Airbnb are among the companies that will be directly impacted by this law. If you do business with EU residents, regardless of geographic locality, this law directly applies to you.

Posted September 20, 2017

Qubole Data Service provides a single platform for ETL, reporting, ad hoc analysis, stream processing and machine learning. It runs on AWS, Microsoft Azure and Oracle Bare Metal Cloud, taking advantage of the elasticity and scale of the cloud, and also supports leading open source engines, including Apache Spark, Hadoop, Presto, and Hive.

Posted September 12, 2017

Columnar Data, Analytics, and the Evolving Role of Hardware

Posted September 12, 2017

New multi-cloud capabilities scale discovery and dependency mapping of all assets to go beyond on-prem data centers to public and private cloud.

Posted September 12, 2017

As organizations increasingly move their data and applications from on-premise deployments to the cloud, the role of the DBA is also shifting. According to Penny Avril, vice president of product management, Oracle Database, the transition means that DBAs have the opportunity to move from being data custodians and keepers to taking on a more strategic role in their organizations. But, she says,the time to prepare for the new cloud reality is now.

Posted September 07, 2017

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