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Developed a data infrastructure for a retail superstore incorporating the advanced data architecture concepts. Defined scalable data models, reduced data redundancy by using junk dimensions and outriggers. Managed efficient data storage policies. Lastly, designed and developed interactive dashboards for sales managers using Tableau.

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ROHANNAIK/Data-Warehouse-and-Business-Intelligence

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Data-Warehouse-and-Business-Intelligence

The key topic areas covered in this project are:

 Data architecture  Dimensional data modeling  Data integration and ETL (extract, transform & load)  Data engineering  BI design

Project focuses on examining the traditional BI appraoch with a Data Warehouse (DW) using relational dbms and the Analytical Data Architecture (ADA) approach that leverages relational, columnar, on-line analytical processing (OLAP), Hadoop and NoSQL databases.

Tools Used for data handling and Data Visualization

Talend, SSIS -- For Data Cleaning

Tableau, Power BI and Qlik --- For Data Visualization

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Developed a data infrastructure for a retail superstore incorporating the advanced data architecture concepts. Defined scalable data models, reduced data redundancy by using junk dimensions and outriggers. Managed efficient data storage policies. Lastly, designed and developed interactive dashboards for sales managers using Tableau.

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