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This project demonstrates my proficiency in using SQL scripts for data exploration, analytics, and reporting. The scripts cover various analyses such as database exploration, measures and metrics, time-based trends, cumulative analytics, segmentation, and more.

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kevkaleido/sql_data_analytics_project

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Sql data analytics project

This project demonstrates my proficiency in using SQL scripts for data exploration, analytics, and reporting. The scripts cover various analyses such as database exploration, measures and metrics, time-based trends, cumulative analytics, segmentation, and more.

Note: This project represents the next step in my data journey, building directly upon the SQL Data Warehouse Project I completed previously. You can explore the SQL Data Warehouse Project here.

Project Structure

The analysis is structured in two progressive phases:

  1. Basic Data Exploration - Foundational queries to understand data structure and core business metrics
  2. Advanced Analytics - Time-series analysis, performance comparisons, and customer segmentation

Key Analytical Areas Covered

  • Database structure exploration and data profiling
  • Core business metrics and KPI calculations
  • Customer demographics and geographic distribution
  • Product performance analysis and rankings
  • Time-series analysis and trend identification
  • Running totals and cumulative metrics
  • Year-over-year performance comparisons
  • Customer segmentation and lifecycle analysis
  • Category contribution analysis
  • Product cost segmentation

Technical Skills Demonstrated

  • Advanced SQL querying and optimization
  • Window functions and analytical functions
  • Common Table Expressions (CTEs)
  • JOINs across dimensional tables
  • Date/time manipulation and analysis
  • Conditional logic and data categorization
  • Performance ranking and comparative analysis

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This project demonstrates my proficiency in using SQL scripts for data exploration, analytics, and reporting. The scripts cover various analyses such as database exploration, measures and metrics, time-based trends, cumulative analytics, segmentation, and more.

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