What’s Popular in Real-time Data Integration

Loraine Lawson

Given the demand for real-time data analytics, it’s not surprising that more organizations are investing in real-time data integration right now. In a TDWI study released earlier this year, real-time data integration rated in the top four reasons IT leaders gave for replacing their existing data integration platform.

But supporting real-time data integration isn’t as simple as investing in a new tool. There are a lot of other things to consider for adopting and using real-time data integration: To be precise, there are 10 rules you’ll need to know, according to Phillip Russom, TDWI’s research director for data management.

If you’re thinking about real-time data integration at all, you really need to read this list. While there are a few obvious rules — like the perennial tech warning to identify a business need first — this list includes a lot of important, unique issues IT leaders can’t skimp on if real-time data integration is going to succeed.

For instance, he points out that often, data integration tasks need to operate at more than one “right time,” so you need to evaluate that and figure out the right deployment times for the tasks. On a related note, real-time data integration speeds can vary, so you’ll need to evaluate the data integration “freshness” requirements on a case-by-case basis.

Another thing I love about this list is he talks about the real-time data integration techniques you need to understand. Here’s my primer on those, for those of you who aren’t DBAs but need to have a basic understanding of the techniques involved:

Federation. Data federation is a form of data virtualization, according to consultant Rick van der Lans. Since the data is mapped back to the original source, it registers changes in real time.

Services. Data services (Web services, but with data) deliver the data through an ESB.

Events. I had to check Wikipedia for this, but event processing lets you monitor streams of data about events. With Complex Event Processing, you can use monitoring capabilities on data from various sources.

These are the three techniques that Russom says are “the most aggressively adopted DI techniques of recent years.”

“Your peers working in other organizations are adopting these; perhaps you should, too,” he challenges.

Tomorrow, I’ll share the remaining three methods that you can use to achieve real-time data integration.

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