You can look at business data lakes three ways:
The first is as one place to put all the data you may want to use. That includes structured data drawn from traditional databases and unstructured data like text. It includes data generated by the enterprise and data imported from outside sources and services. It includes the social media and sensor and telemetry data that’s being generated in vast quantities and that most enterprises are just learning to work with.
The second way is as a platform for big data analytics. A data lake isn’t just a landing zone for all sorts of data. It’s where you can analyze the data as well, and where you can find the correlations among data that you’ve never before examined together. Many of the breakthroughs with business analytics come not just through looking at more data or doing more sophisticated analyses, but through new combinations of data that reveal the drivers of business performance.
The third is to use data lakes as a way to help resolve the long-standing tension between the corporate push to get standard data into warehouses and used consistently, and the business unit need for local views and combinations of data that get implemented in all those Excel spreadsheets. A data lake is a shared resource, and it may contain a lot of carefully administered data. But it also provides a platform for business units to get at the data and quickly build the views and data-driven applications they really need.
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