SQL on Hadoop Evaluation Guide

March 23, 2015

SQL-on-Hadoop solutions have become very popular recently as companies solve the data access issues with Hadoop or seek a scale-out alternative for traditional relational database management systems. However, with all of the options available, choosing which solution is right for your business can be a daunting task.

Gigaom Analyst Report: The Power of Hadoop as a Service

March 18, 2015

This industry analyst report takes up important considerations when planning a Hadoop implementation. While some companies have the skill and the will to build, operate, and maintain large Hadoop clusters of their own, a growing number are choosing not to make investments in house and are looking to the cloud.

Big Data Beyond the Hype: A Guide to Conversations for Today’s Data Center

March 13, 2015

The term big data is a bit of a misnomer. Truth be told, we’re not even big fans of the term—despite its prominence—because it implies that other data is somehow small (it might be) or that this particular type of data is large in size (it can be, but doesn't have to be).

Improving Analytics and Reporting with Near-Real-Time Data Replication

March 13, 2015

Your business relies on data analytics for business intelligence, but if the data isn’t up to date, the analytics is worthless. In this technical brief, see how to replicate real-time data, whether it’s on site, remote, or in the cloud.

Real-Time Data Visualization: Do It Live!

March 13, 2015

This Aberdeen research report examines the decision-making benefits of real-time visualization and explores the technologies that help live data drive superior performance.

Achieving World-Class Collaboration—A Three-Step Process for Bringing Your Architects, Developers and DBAs Together

March 13, 2015

Learn the three steps to successful collaboration—thinking, moving, and governing as one—and about software to make it happen.

Big Data Comes of Age: Shifting to a Real-Time Data Platform

March 13, 2015

In 1959, famed business thought leader Peter Drucker coined the term knowledge worker, defining it as "one who works primarily with information or one who develops and uses knowledge in the workplace.” As forward thinking as Drucker was, he might be surprised at the level of sophistication today’s data-driven executives are applying to critical business challenges. Google-generation knowledge workers arrive in the enterprise with an expectation of speed, power, and ease of use, and they are comfortable putting these assets to work on analytic and operational data-driven projects.