# ptyadana/SQL-Data-Analysis-and-Visualization-Projects

SQL data analysis & visualization projects using MySQL, PostgreSQL, SQLite, Tableau, Apache Spark and pySpark.

Repository: https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects
Canonical: https://ross.abutalabs.com/products/sql-data-analysis-and-visualization-projects
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: sql, mysql, mysql-notes, exercises, mysqlworkbench, mysql-database, data-analysis, postgresql, postgres, sqlite, pgadmin, tableau, challenges, digital-music-store, sql-queries, sql-data-analysis, python, pyspark, apache-spark
Last push: 2022-07-18T12:05:11+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2377, "days_push": 1507, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1809, forks 579 (observed 2026-08-28T04:05:39.429696+00:00)

## What it is
A compilation of SQL data analysis and visualization practice projects and challenges using MySQL, PostgreSQL, SQLite, Tableau, and Apache Spark with pySpark. It includes real-world style business scenarios such as an Instagram clone database, film rental store, employee analytics, and digital music store analysis.

## Use cases
- practice sql queries with real-world business scenarios
- learn mysql postgresql and sqlite through projects
- analyze a cloned instagram database with sql
- visualize employee data with tableau
- learn pyspark and apache spark for data analysis
- find sql exercises and challenges for data analysis
- answer business questions with sql data analysis

## When to choose
- you want hands-on SQL practice projects with business scenarios
- you are learning MySQL, PostgreSQL, SQLite, Tableau, or pySpark
- you need example datasets and guided challenges for a data analysis portfolio

## When to avoid
- you need production-ready data analysis software or a library to import
- you want an automated analytics tool rather than educational notebooks
- you need up-to-date content, as the latest release was in 2022

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, data-visualization, database, etl
- domain: data-science, data-visualization, databases, education, tutorials
- platform: python, cross-platform
- tags: sql, mysql, postgresql, sqlite, tableau, pyspark, apache-spark, jupyter-notebook, practice-projects, sql-exercises

## Member repositories
- ptyadana/SQL-Data-Analysis-and-Visualization-Projects (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.429696+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:20.231784+00:00, confidence not recorded.
  - readme: https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects (fetched 2026-08-28T04:05:39.429696+00:00, sha 2674ac697a16)
- Data as of 2026-08-30T08:39:29.467469+00:00.