SQL / ETL: Insurance Claims Analysis Project

Objective: To analyze insurance claim data to gain insights and improve database performance.

CRISP-DM Process:

• Business Understanding:

  Objective: Analyze insurance claim data for insights.

  Goals: Create a database schema, populate with sample data, analyze claims, optimize performance, and manage database security.

• Data Understanding:

  Data Sources: Insurance data including customers, policies, claims, and policy types. Initial Exploration: Understand relationships between tables and the types of data available.

  
  

• Data Preparation:

  Create Schema: Defined tables for customers, policies, claims, and policy types.

  Populate Data: Inserted sample data into the tables to ensure a variety of data types for analysis.

  
  

• Modeling:

  Analytical Queries: Wrote SQL queries to calculate total claims per policy type and determine monthly claim frequency and average claim amount. Index Creation: Optimized performance by creating indexes on frequently queried columns.

  
  

• Evaluation:

  Query Results: Evaluated the results of the analytical queries to ensure they met the project objectives. Performance: Assessed the effectiveness of the indexes in improving query performance.

  
  

• Deployment:

  Roles and Permissions: Set up roles such as ClaimsAnalyst and ClaimsManager with specific permissions to ensure database security.

  Final Review: Ensured the database was secure and performed efficiently with the implemented roles and permissions.

  
  

  Outcome:

  A well-structured database with relevant sample data.

  Analytical insights into the number of claims per policy type and monthly claim trends. Improved database performance through indexing.

  Enhanced database security with well-defined roles and permissions.