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DataFrame Explorer

SQL Frames makes it possible to create complex data transformations using familiar SQL constructs which allows users to declaratively filter, aggregate and pivot data. Complex SQL constructs such as ROLLUP, CUBE and subqueries can be used to create the desired reports.

Most analytic solutions only provide the final result of the transformations since they only generate the final SQL (or for anything complex ask the user to directly write the SQL). SQL Frames on the other hand is able to make use of the low-code API based data transformation logic intelligently and provide a rich user experience for data exploration without writing a single line of code! It provides the ability to view the data at every step of the transformation such as joins, filters and aggregations to better understand the data behind the numbers. This is all provide with the simple df.ui.explorer API as shown below.