Enterprise Resource Planning (ERP) systems promised enterprises that it would make it easier to do business. Instead, enterprises got an information hegemony that today does anything but. The idea was that the systems would track resources and business commitments in…
It’s Friday afternoon. You’ve left your cape and utility belt in the office, and are heading home for a weekend of socializing. You will keep friends and families on the edge of their seats with stories from the front-ish lines…
Data mastering (sometimes called Master Data Management or MDM for short) is now 15 years old. It arose because enterprises have been creating independent business units (IBUs) for a long time with substantial freedom of action. This allows IBUs to…
The task of keeping citizens safe in an environment where global security is increasingly a concern is complicated. It requires collecting, processing, querying, and constructing massive amounts of data to screen individuals against risk criteria for threat prevention, public health,…
Data variety — the middle child of the three Vs of Big Data — is in big trouble. It’s in the critical path of enterprise data becoming an asset. And it’s been slow to benefit from the kind of technology…
If you’ve been following Tamr’s content for a while, then chances are you’ve heard us talk about DataOps — the automated, process-oriented methodology aimed at increasing analytic outcomes across an organization. And as large enterprises continue to generate a tremendous…
Every decade there are three or four new systems who federate data in disparate systems. This has been a regular occurrence for the last forty or so years. In fact, I am responsible for proposing one in the 1970’s (Distributed…
Getting effective new drugs to patients quickly is the lifeblood of every pharmaceutical company, and success in the endeavor hinges on analytical capabilities. The issue: as pharma companies grow and evolve, their data—especially R&D data—is often kept within silos created…
Great analytic dashboards require great data. This places a heavy burden on analytic developers, who are rarely given perfect data that aligns with their users’ expectations. Data variety makes it challenging to easily assess if data is fit for consumption.…
If your organization is like most, then the variety, volume, and velocity of the data you regularly collect is creating challenges when it comes to: Leveraging that data to inform business-driving decisions Getting real-time data access to everyone in the…
