by Angela Guess
In a recent interview, James Markarian noted five key issues that should be addressed by a Big Data integration platform. The first issue was “Integration from a variety of sources, from mainframes to messaging systems. ‘These big data processing environments aren’t the originators of the information,’ he said.”
The second issue Markarian suggested was data quality and data governance: “You have to be able to trust the data if you’re going to use it for analytics or decision making, he warned, and that means a Big Data platform has to support data quality and data governance. ‘We view data quality as being even more important in the big data environments because small problems with information and information-handling can result in large magnification of errors,’ he told me.”
A third key issue to address is text analytics and sentiment analysis: This “means being able to put context around the data you’re receiving. For instance, when processing millions of feeds, you need to be able to decide whether that information is something you care about. That may mean integrating the data with your MDM system or another enterprise application, he said. Then you need to put that information into context. For instance, is the comment positive or negative? Does it represent a trend? ‘That’s where something like the combination of text analytics combined with identity resolution so that you can match that information against your existing enterprise systems comes into play,’ he said.”
photo credit: monkeymanforever
