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
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.