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Shaping Your Data with SQL
Improve & optimize your data analytical process with different techniques for data shaping
Why is Data Shaping?
There is no one-size-fits-all data. For different purposes and used cases, data is customized accordingly. The more you are aware of the intended use of data afterward, the more equipped you will be to correctly present your data to the end users.
For example, the data utilized to undertake in-depth analysis differ from the aggregated data provided to upper management.
Another example, the business development team is more concerned with the overall cost per area to convert new users than the marketing managers are with affiliate marketing costs, which they want to look at specifically by region.
That being said, transforming existing data structures into any alternative pivoted or unpivoted structure is an indispensable step in any data manipulation and analytical process.
In this article, I will introduce a few techniques to shape and slice your data in some specific cases. Usually, I will present my examples with PostgreSQL.
Now, let’s start to see what we’ve got!
