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Data_Visualization

Using Tools like Tableau is a great way for EDA (Exploratory Data Analysis) to perform initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of graphical representations.

TabPy for Predictive Analytics

On the other hand, Tableau brings everything together in a visual environment that’s accessible to anyone functioning as a dashboard for supply chain analytics. Moreover it supports advanced predictive modeling and forecasting that can be connected to TabPy Server for Enterprise needs. Tableau opens an elegant and powerful view into an organization existing metrics as well as allowing us to create new, customized algorithms supported with Python or R languages in TabPy & RServe. See how Tableau enhances your supply chain analytics below. Streamlining the supply chain means managing multiple complex factors all at once, in real time: optimizing inventory, streamlining transportation, and delivering just in time, every time.

GI_RGI_Analysis

TabPy Server Running for Tableau Connections

TabPy (the Tableau Python Server) is an Analytics Extension implementation which expands Tableau's capabilities by allowing users to execute Python scripts and saved functions via Tableau's table calculations. Hence, TabPy is what is required to support predictive modeling (ie: supervised learning - Linear Regression or unsupervised learning such as clustering) in Python sci-kit learn packages.

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TabClient Connection String in Python Script to connect to TabPy Server

https://help.tableau.com/current/prep/en-us/prep_scripts_TabPy.htm

Python script using ARIMA forecasting to display in Tableau visualization

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Hypothesis Testing (A/B Testing)

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Correlation between Sales and Discount

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