Even if you analyze your data in real time, storing data for extended periods is important for compliance and other reasons. But what types of data should be retained and how long should you keep it?...
There are some very good reasons why many of the world’s most transaction-intensive companies are still running critical business applications on mainframes and using legacy data. Those legacy...
Data is at the heart of every real estate decision, whether you’re an investor or buyer. What makes a property unique is everything from the type of flooring to the township it sits in....
The 2020 Spark+AI Summit 2020 organized by Databricks hosted 60,000 virtual attendees. The keynotes focused on technical updates such as data integration and quality, and included multiple live...
You know a data quality strategy is important. But do you know how to assess how good of a job your company is doing at achieving data quality? Keep reading for tips on developing a data quality...
Developing a data quality framework is reminiscent of herding cats. You have to bring together disparate groups to establish a set of standards to maintain data quality, when these groups don’t...
No one can afford downtime. There’s a problem, though: infrastructure is incredibly complex. There are many systems and networks that depend upon one another to support a single business...
Modern data analytics tools make it possible to apply context to data in a myriad of distinct ways. Historically, data analysts have aggregated consumers into broadly defined groups. Nielsen Media...
IBM’s security implementation on the IBM i platform is good, but that doesn’t mean that it’s immune from data breaches. All PCs and servers on the same network as your IBM i server are...
