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February 2017, Vol. 5, No. 1

Fast-moving big data changes data preparation process for analytics

The beneficial connection between preparation and opportunity has been noted by more than a few sages, from the Roman philosopher Seneca to American self-help entrepreneur Tony Robbins. But data preparation's role in the opportunity known as big data analytics is often underappreciated, if not overlooked completely. The data preparation process can be a stumbling block that stands between advanced analytics technologies and the business benefits organizations hope to get from them -- increased revenues, more efficient operations, better decision-making and more. And as big data environments proliferate, the work involved in integrating and preparing data for analytics uses is changing in some notable ways. On the front end, there are more -- and more diverse -- sources of data with which to work. All that variety spices up the big data analytics stew, but it upends traditional data pipelines. The days of a one-directional data flow into an enterprise data warehouse are ebbing; in the big data world, data often needs to move back...

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