Big data is structured, semi-structured, un-structured, and raw data in many different formats, in some cases looking totally different than the clean scalar numbers and text you have stored in your data warehouses for the last 30 years. Much big data cannot be analyzed with anything that looks like SQL. But most important, big data is a paradigm shift in how you think about data assets, where you collect them, how you analyze them, and how you monetize the insights from the analysis.
The big data movement has gathered momentum as a large number of use cases have been recognized that fall into the category of big data analytics.
Big Data is not only about the data within the corporate firewalls but also about data outside the firewalls too. Hidden inside these vast reservoirs of data are insights that are waiting to be exploited for favorable business outcomes.
Big data’s bigness is hardly the interesting characteristic. The real fun lies in how we think about data, where they reside in the data ecosystem and how do we generate value from them.
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