How adhavar/grocery-sales-analysis-visualization works
This repository documents a SQLite workflow for turning grocery transaction CSVs into validated, joined analytical data, then querying sales performance for a Tableau dashboard. The domain stages are schema creation, data validation, analytical-table construction, and business analysis; the visualization is a downstream product capability. Relationships are based on the README only, since no SQL excerpts were provided, so query-level details and dashboard data connections are not inferred.
Main entry points: 1_create_tables.sql Source Tables · 3_join_and_selection.sql Analytical Table · 2_data_validation.sql Data Validation · 4_data_analysis.sql Sales Analysis
Components 7
Data Preparation
- Source Tables
sql/1_create_tables.sql - Data Validation
sql/2_data_validation.sql - Analytical Table
sql/3_join_and_selection.sql
Sales Analysis
- Sales Analysis
sql/4_data_analysis.sql
Visualization
- Tableau Dashboard
Other components
- Grocery CSVs
- SQLite
Connections 10
- Grocery CSVs → Source Tables: imported into
README.md - Source Tables → Data Validation: validated by
README.md - Source Tables → Analytical Table: joined into
README.md - Data Validation → Analytical Table: cleaned for
README.md - Analytical Table → Sales Analysis: queried by
README.md - Sales Analysis → Tableau Dashboard: results validate
README.md - SQLite → Source Tables: creates tables
README.md - SQLite → Data Validation: runs queries
README.md - SQLite → Analytical Table: transforms data
README.md - SQLite → Sales Analysis: runs analysis
README.md