Browse realistic synthetic datasets
Choose a business dataset with clear row grain, coherent relationships, protected realism rules, and dashboard-ready CSV or JSON exports.
Choose by business question
Every active generator remains visible because five documented datasets do not need search or filtering. Choose the row grain that matches the analytical decision.
- Ecommerce Sales Dataset Generator — One row = one product line · 32 fields
- Support Tickets Dataset Generator — One row = one support ticket · 25 fields
- HR Analytics Dataset Generator — One row = one employee snapshot · 32 fields
- SaaS Subscriptions Dataset Generator — One row = one subscription month · 32 fields
- Marketing Campaigns Dataset Generator — One row = one campaign-channel day · 33 fields
Compare the analytical contract before the file
All five active datasets stay visible. Compare row grain, core analysis signals, and difficulty before opening a generator.
| Dataset | Row grain | Core signals | Difficulty |
|---|---|---|---|
| Ecommerce Sales | One row = one product line | Net revenue / Weighted margin / Distinct orders | Beginner |
| Support Tickets | One row = one support ticket | Active backlog / SLA breach rate / Avg. response | Beginner |
| HR Analytics | One row = one employee snapshot | Headcount / Attrition rate / Avg. tenure | Intermediate |
| SaaS Subscriptions | One row = one subscription month | Current MRR / Net movement / Active subs | Advanced |
| Marketing Campaigns | One row = one campaign-channel day | Media spend / Blended CPA / Weighted ROAS | Intermediate |
Practice with a complete Power BI workflow
Follow the Power BI dashboard practice workflow for dataset selection, modeling, measures, validation, and portfolio guidance.
Dashboard-ready business datasets
5 active datasets cover sales and revenue, customer operations, people analytics, and subscription analytics without exposing planned or unfinished templates.
Built for beginners and professional analysts
Start with protected business scenarios and guided dashboard recipes, or use reproducible seeds, fixed anchor dates, copy-ready BI measures, and dashboard starter kits for advanced practice.
Realistic structure before random volume
Every public dataset documents its row grain, identifiers, lifecycle rules, null behavior, calculations, exports, and BI interpretation guardrails.