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Big Data: Businesses Procrastinate with Data Lakes
Data silos have long been a nemesis of businesses trying to fully utilize the data which they collect. Recently ‘data lakes’ have been proposed as a solution for eliminating the silos. The data lake is an aggregate of data with no attempt made to transform it to some common format. Even if the data isn’t used today, by keeping it in the data lake, it can some day later be used for analysis. But Gartner says that this approach has problems and effectively is procrastination: businesses are merely hoping that the data that they put into the lake will become usable and valuable at some point in the future.
Nick Heudecker, research director at Gartner, said that “data lakes are marketed as enterprise-wide data management platforms for analyzing disparate sources of data in its native format. The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it’s available for analysis by everyone in the organization.”
Andrew White, VP and distinguished analyst at Gartner, said that “the need for increased agility and accessibility for data analysis is the primary driver for data lakes. Nevertheless, while it is certainly true that data lakes can provide value to various parts of the organisation, the proposition of enterprise-wide data management has yet to be realised.”
Gartner argues that there are risks with adopting data lakes and suggests that for now businesses stick with more traditional techniques, like data warehousing. While data warehousing requires that data be extracted, transformed and then loaded into a central repository, that extra effort will make data more usable and valuable to businesses.
