Combination of Tableau and Python for Prescriptive Analytics with Tabpy

What is TabPy

TabPy is a Python package that enables students of top engineering colleges to execute Python code on the fly and display results in Tableau visualizations. It results in the quick expansion of advanced analytics applications. The split approach provided by TabPy allows for the better of two worlds including class-leading data visualization capabilities that are mainly backed by powerful data science algorithms.
Surfacing Python algorithms in Tableau allows users to tune parameters and evaluate their impact on the analysis in real-time with the updates of the dashboard. In order to make this possible, TabPy mainly provides an input/output approach to the students of best engineering colleges. Where the data is aggregated according to the current visualization and tuning parameters, both transferred to Python. The data is processed and an output is sent back to Tableau to update the current visualization.
TabPy offers an approach that helps students of Engineering Colleges in finding the full power of TabPy for the following scenarios including:
Real-time interaction
If students of computer science engineering at Best Engineering College Jaipur require having a real-time user interface, they must minimize the processing time and delay between a parameter change and updated visualization.
Multiple levels of aggregation
If an individual wants to show different aggregation levels on the same Tableau dashboards, they must perform all the calculations using the finest and most granular level that contains all information.
Various data sources
The backend calculation mainly relies on more than a single data source or database.
Data transferred between Tableau and Python
It requires a significant amount of data for each optimization step. Therefore, it is essential to transfer lots of data between Tableau and the Python backend.
A novel by approach for prescriptive analytics ?????
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