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February 2017, Vol. 5, No. 1

Data preparation steps increase to meet predictive analytics needs

In more and more businesses, the drive to set up big data architectures that can support predictive analytics, data mining and machine learning applications is changing the shape of the data pipeline as well as the data preparation steps required to feed it. "We used to live in a very straightforward world where data moved in one direction -- it was a data flow into a data warehouse," independent consultant and industry analyst Dave Wells said. "Now we have data warehouses, data lakes and data scientists' sandboxes. There are many sources, and they're processed in many ways. And the data pipelines now are multidirectional." The overall effect is that strictly linear approaches to data flows are breaking down. And data scientists and other users whose analytical interests are exploratory or discovery-oriented in nature must be served by data management teams, explained Wells, who wrote a report on data preparation software and tools for managing data pipelines that was published last November by consulting firm Eckerson Group. ...

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