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How Google Big Query Changed the Game

For the past few decades, the approach to data analysis and storage has been standard without much innovation in the database warehouse technologies. Previously, the process of joining large data sets from various sources for analysis and reporting was laborious and cost in-effective. The entire ETL process, both internal and external, in its usual form is time-consuming because of the various process involved like designs, approvals, governance, etc.

It also sees itself becoming obsolete as datasets keep going bigger and bigger. Another problem that arises is the storage of such large quantities of data.

The solution to this is a new innovation in the market, public datasets. This is a revolutionary new step in the world of data access. These provide the end-user a one-stop-shop for all their data analysis and reporting needs without the hassles of planning, approvals, testing, etc. The only barrier between the data and the user is the permission restrictions, which can all go away for a monetary fee.

In the long run, this allows organizations to save tremendously on the time costs and effectiveness of their usage of data without the worry of managing and storing datasets that might have been otherwise out of control.


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