Descriptive Database Data Analysis - 14/08/2026 15:33 EDT

I need a concise descriptive analysis of the data currently stored in my relational database. The tables are already structured and populated; what I lack is a clear, statistics-driven snapshot that highlights key totals, averages, distributions, and any obvious trends or anomalies.

You’ll connect directly to the database (credentials supplied after award) and:

• explore table relationships and data quality,
• run summary statistics and frequency counts,
• create straightforward visualizations—think bar plots, histograms, heat-maps—that quickly communicate the story behind the numbers,
• package everything into a short, well-commented Jupyter Notebook (or SQL script plus slides, if you prefer) so I can reproduce the results at any time.

Please keep the focus on descriptive methods; no predictive modelling is necessary. Familiarity with SQL, pandas, and a visualization library such as Matplotlib or Tableau will speed things along. I’m aiming for clarity over complexity, so clean, well-labelled outputs are more important than advanced techniques.

When you reply, let me know roughly how many hours you estimate for an initial pass and which tool you would use to present the findings.