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In this project, I focus on building a sales data mart for a company by extracting new and updated data from the AdventureWorks2019 (OLTP data) database, creating a star schema and load data to dimensions and fact tables after transforming the data, and finally applying full, incremental, and slow-changing dimension (SCD) loading.

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Building Sales Data Mart

intoduction:

In this project, I focus on building a sales data mart for a company by extracting new and updated data from the AdventureWorks2019 (OLTP data) database, creating a star schema and load data to dimensions and fact tables after transforming the data, and finally applying full, incremental, and slow-changing dimension (SCD) loading.

Data Mart: is a subject-oriented database that is often a partitioned segment of an enterprise data warehouse.

Data Source:

using AdventureWorks2014 (OLTP) from microsoft source.

steps:

  1. Data Modeling by creating star schema for the data mart:

star schema

  1. Slowly Changing Dimension (SCD)

SCD

  1. Full load to fact sales table

Full load

  1. Increamental load for new records updated to the source database.

increamental load

About

In this project, I focus on building a sales data mart for a company by extracting new and updated data from the AdventureWorks2019 (OLTP data) database, creating a star schema and load data to dimensions and fact tables after transforming the data, and finally applying full, incremental, and slow-changing dimension (SCD) loading.

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