New Data Challenges Drive Need for Updated Integration Strategy

Loraine Lawson
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Four Steps to a Big Data Strategy

In recent years, more IT organizations have shifted away from hand-coding integration to using a data integration tool.

In theory, that should eliminate some of the spaghetti code going forward. The problem, though, is that times have changed and the data integration tools of yesterday may no longer be enough, contends integration and data consultant David Linthicum.

In particular, Big Data and cloud computing are creating new challenges that may require organizations to re-think their current data integration strategy, Linthicum writes in a guest blog for Actian, a Big Data solution provider that offers an integration platform for the cloud.


In particular, Linthicum points to Big Data, noSQL, the cloud, and the complexity of data as reasons why CIOs need to evaluate how the IT division currently handles data integration.

“The bottom line is that our data environments are becoming more complex and distributed, and this trend will continue for at least the next 10 years,” Linthicum writes. “Enterprises will continue to see the need and importance of data integration solutions, and thus it continues to be a priority in most IT shops that think proactively.”

Assess your existing data integration solutions’ readiness for this new distributed, data-rich environment by asking the following:

  • Does your current solution support real-time data or are you still moving data in daily or weekly batches? Data needs to change as it moves now, and that will require a reliable integration solution that uses an exception management layer to handle exceptions, Linthicum explains.
  • Can your integration tools handle large volumes of data? You’ve heard time and time again that organizations now hold massive amounts of data. It’s easy to hear that and think about storage, but that data isn’t just gathering dust. Much of it is in motion, coming and going from place to place for analysis. That means you have to be able to integrate and move large volumes of data, as well as store it.
  • Can your data integration tool work with the security safeguards used in distributed computing? For instance, identity management is a must-have security measure in the cloud, but not all data integration tools can handle it.
  • Can you pull data in and out of Big Data silos, such as Hadoop Distributed File Systems? Jim Harris, a data management consultant, points out in a recent blog post that Hadoop and other NoSQL solutions can do a lot with data, but by themselves, they’re silos.

“So, yes, it’s great that you can pull in, for example, social data about what your customers are saying about your products on Twitter and Facebook, but if that data is antisocial (i.e., not integrated) with the data about your customers and products in MDM and the data warehouse, then what use is it?” he asks.

Many data integration tools today are shipping with connectors for Hadoop and other Big Data tools, but you need to make sure your data integration solution will allow you to move data from your Big Data/cloud store of choice.



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