The document discusses a customer churn analysis project for Barclays bank. It provides details about Barclays as a multinational bank and describes responsibilities like collecting data from various sources, performing data mining and profiling, transforming data, and generating reports in Power BI for senior management. The end-to-end process involves data modelling and analysis to understand customer behavior and identify at-risk customers.

1. CUSTOMER CHURN ANALYSIS

2. BARCLAYS:
• Barclays is a British multinational investment bank.
• It has over 4,750 branches, including more than 3,000 outside Britain
in 50 countries.
• It is headquarted in London.
• Its market value is 28 Billion Pounds.

3. RESPONSIBILITIES & DAILY TASKS:
• Collect data from various sources such as CRM, ERP, Excel Files, CSV Files, SQL DB and
migrate it to the central cloud database i.e. Azure Synapse where we maintained all the
data of the Customer Churn Analysis.
• Perform Data Mining and Data Profiling using various SQL Query Techniques.
• Extract Data from the source to Azure Data Factory by developing Pipelines.
• Transformation of Data such as filtering, sorting, aggregating, joining. cleaning, &
validating data.
• Creation of Cubes in Power BI of SSAS using Fact and Dimension Tables(Star Schema).
• Maintaining the history of the data and storing the data in Azure Data Lake or Blob
Storage.
• Designing the database using Star Schema for reporting purposes.
• Event based Triggers were set up for new incoming data to be loaded to Azure Cloud
Blob Storage.
• Audited existing pipelines and packages for errors and failures to report.
• Generating reports and presenting to the senior management using Power BI to facilitate
decision making process.

4. END TO END PROCESS:

5. DATA MODELLING: