Читать книгу Data Lakes For Dummies - Alan R. Simon - Страница 36

Maybe your organization has been dabbling in the world of big data for a while, going back to when Hadoop was one of the hottest new technologies. You’ve built some pretty nifty predictive analytics models, and now you’re fairly adept at discovering important patterns buried in mountains of data.

So far, though, your AAA — adventures in advanced analytics — have been highly fragmented. In fact, your analytical data is all over the place. You don’t have consistent approaches to cleansing and refining raw data to get the data ready for analytics; different groups do their own thing. It’s like the Wild West out there!

The concept of a data lake helps you harness the power of big data technology to the benefit of your entire organization. By following emerging best practices, avoiding traps and pitfalls, and building a solidly architected data lake, you can seize the day and help take your organization to new heights when it comes to analytics and data-driven insights.

You’ll achieve economies of scale for the data side of analytics throughout your organization, which means that you’ll get “more bang for your buck” when it comes to acquiring, consolidating, preparing, and storing your analytical data on behalf of your enterprise as a whole rather than repetitively doing so for numerous smaller groups.