The Data Lake Data Integration Challenge

The future for big data processing lies in the adoption of commercial Hadoop distributions and their supposed deployments. The macro use case for big data are data lakes, which are massive amounts of structured and unstructured data that do not carry the same restrictions as traditional data warehouses. They store everything, including every type of data, any volume, any scope of data that may be used by enterprise data users, for any reason.

Despite the power and potential of data lakes, many enterprises continue to approach this technology with the same data integration approaches and mechanisms they’ve used in the past, none of which work well. How can we tap into the power of the data lake? 

Read this whitepaper by industry analyst David Linthicum to learn how using a data integration service can handle both structured and unstructured data. Now comes the need for schema-less data storage, the ability to deal with streams of data that function in real time, and an entirely different approach to data integration that involves newer data integration technology.

From David Linthicum:

“The reality is that data lakes require data integration solutions that can deal with structured and unstructured data, as well as deal with schema-less data storage. They also need to deal with streams of data that function in real time. In other words, a data lake requires a completely different approach to data integration, and it needs newer data integration technology to drive success.”

You can read the whitepaper on our Resources page  and learn more about SnapLogic’s data integration services for the modern enterprise. SnapLogic is the #NewIntegrationLeader and enables you to connect easier and faster to accelerate your business.

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