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Supermarket Data Analysis

Open source Python
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BI Dashboards DevOps & Infrastructure

 About Supermarket Data Analysis

This is a business intelligence project on analyzing super market data. Check out the README file for more details.

Platforms

Web Self-hosted

Languages

Python

Links

Source Code

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Supermarket Data Analysis

View on GitHub

Supermarket-Data-Analysis

Technologies used:

  • Business Intelligence
  • Database
  • Python
  • Tableau

The .csv files are a based on the dataset uploaded by walmart on Kaggle.The dataset is divided into 3 tables: Customer, Product & Transaction (all in .csv format). The tables have their own 'primary key' or 'table_id'. They are combined to form FACT table. The csv files are loaded into SQL tables on localhost using commands given in file : prachidbcommands.txt
The SQL is connected with python to display all tables using the python code given in: prachidbconnect.py OLAP operations that are applied on the Fact table are- Slicing, Roll up, Pivot, Min & max Machine learning algoritm- KMeans is used to analyse the data. The code is given in : prachikmeans.py and output is shown in prachikmeans.png Tableau is used to visualize the data in geomaps, line chart, bar chart and motion chart. The tableau file is: prachibivisualization.twb and respective images of visualisations are uploaded as- prachilinev.PNG, prachimotionv.PNG, prachigeov.PNG and prachibarv.PNG