Читать книгу Data Lakes For Dummies - Alan R. Simon - Страница 56

Jan, your CPO, is thrilled with the work that Raul and his team have done compiling the HR analytics continuum. They’ve produced an exhaustive list of more than 500 analytical functions that will be supported by the data lake, covering the broad continuum from simple “What happened?” descriptive analytics through more than a dozen complex prescriptive analytics scenarios.

Now what?

As you might guess, that 500-plus master list of HR analytics isn’t going to be available the first day your data lake goes operational. A data lake is built in a phased, incremental manner, probably over several years.

But where to start?

In Chapter 17, I show you how to build your road map that will take you from your first ideas about your data lake all the way through multiple phases of implementation.

Your data lake road map should be driven by your organization’s analytical needs rather than by available data. You should address your highest-impact, highest-value analytics needs first, for two reasons:

 You need the initial operating capability (IOC) of your data lake to come with some “oomph.” In other words, you want people across your organization to sit up and take notice that the data lake is, from its first days, providing some really great analytics.

 You want to build your data lake using a “pipeline” approach that not only loads your data lake with lots of data but carries that data all the way through to critical business insights.