An enterprise-grade, Tableau-replica analytics platform that runs entirely in a single HTML file — no installation, no server, no subscription, no internet required.
🚀 Open Live App · 📖 Feature Guide · 🐛 Report Bug · 💡 Suggest Feature
Adewale Samson Adeagbo is embedded across the application interface and all documentation as the creator and owner of Tableau Stimulator Enterprise.
| Item | Details |
|---|---|
| Name | Adewale Samson Adeagbo |
| Location | Lagos, Nigeria 🇳🇬 |
| Identity | Data Scientist · STEM Educator · EdTech Builder · AI-Augmented Solutions Developer |
| Experience | 15+ years teaching Nursery, Primary and Secondary learners across Mathematics, Further Mathematics, Physics, Chemistry and Computer Science |
| Education | B.Sc.(Ed) Computer Science Education, Lagos State University, 2023 |
| Brand | Founder / Visioner of HMG Concepts — HMG Academy, HMG Technologies and HMG Media |
| Portfolio | cssadewale.pages.dev |
| HMG Concepts | hmgconcepts.pages.dev |
| HMG Academy | hmgacademy.pages.dev |
| GitHub | github.com/cssadewale |
| linkedin.com/in/adewalesamsonadeagbo | |
| YouTube | youtube.com/@hmgconcepts |
| +234 810 086 6322 | |
| hmgconcepts@gmail.com · hismarvellousgrace@gmail.com |
Inside the app: Users see the creator's name in the Enterprise Status Bar, the topbar badge, the About modal, the Enterprise Footer, and the splash screen.
Enterprise Edition preserves every feature from the original Tableau Stimulator and adds 16 new enterprise-grade capabilities:
| # | Enterprise Feature | What It Does | Tableau Equivalent |
|---|---|---|---|
| 1 | Treemap Chart | Hierarchical area visualization — rectangle sizes represent values | Tableau Treemap |
| 2 | Sunburst Chart | Multi-level radial hierarchy with drill-down | Tableau Sunburst |
| 3 | Sankey Flow Diagram | Flow/relationship visualization between categories | Tableau Flow / Sankey extension |
| 4 | Parallel Coordinates | Multi-dimensional comparison across all numeric fields | Tableau Parallel Coordinates |
| 5 | Bubble Chart | Scatter plot with size encoding for 3-variable comparison | Tableau Bubble |
| 6 | Nightingale Rose | Polar area chart for cyclical data magnitude comparison | Tableau Rose chart |
| 7 | Histogram | Auto-binned frequency distribution | Tableau Histogram |
| 8 | Bullet Chart | Actual vs target with quality range bands | Tableau Bullet Graph |
| 9 | Data Stories / Storyboard | Capture charts as story points with captions, navigate, export | Tableau Story |
| 10 | Explain Data | Algorithmic insights engine — no AI API | Tableau Explain Data |
| 11 | Linear Regression | Full OLS regression with R², slope, intercept, standard error | Tableau Trend Model |
| 12 | K-Means Clustering | Unsupervised grouping, adds _Cluster field to data | Tableau Clustering extension |
| 13 | Enterprise Export Center | 9 export formats in a unified hub | Tableau Export menu |
| 14 | Row-Level Security | Restrict visible rows by field value — governance simulation | Tableau Server RLS |
| 15 | 4-Column Dashboard | Dense enterprise dashboard grid layout | Tableau Dashboard Layout |
| 16 | SVG Vector Export | Scalable vector graphics for print-quality output | Tableau SVG export |
All 16 features are free, local, use no AI API, and require no paid service.
| Category | Features |
|---|---|
| Original Tableau Stimulator features | 75+ |
| Enterprise Edition additions | 16 |
| Total features | 90+ |
| Chart types (original) | 15 |
| Chart types (enterprise) | 8 additional |
| Total chart types | 23 |
| # | Chart | Type | Best For |
|---|---|---|---|
| 1 | Bar | Original | Comparing categories |
| 2 | Horizontal Bar | Original | Long category names |
| 3 | Stacked Bar | Original | Sub-category contribution |
| 4 | Line | Original | Trends over time |
| 5 | Area | Original | Volume trends |
| 6 | Stacked Area | Original | Cumulative flows |
| 7 | Scatter | Original | Correlation |
| 8 | Pie | Original | Part-of-whole |
| 9 | Donut | Original | Part-of-whole (arc) |
| 10 | Radar/Spider | Original | Multi-attribute profiling |
| 11 | Heatmap | Original | 2D intensity |
| 12 | Box Plot | Original | Distribution + outliers |
| 13 | Waterfall | Original | Incremental changes |
| 14 | Funnel | Original | Staged conversion |
| 15 | Gauge | Original | KPI vs range |
| 16 | Treemap | Enterprise | Hierarchical area |
| 17 | Sunburst | Enterprise | Multi-level radial |
| 18 | Sankey | Enterprise | Flow/relationship |
| 19 | Parallel Coords | Enterprise | Multi-dimensional |
| 20 | Bubble | Enterprise | 3-variable scatter |
| 21 | Nightingale Rose | Enterprise | Polar magnitude |
| 22 | Histogram | Enterprise | Frequency distribution |
| 23 | Bullet | Enterprise | Actual vs target |
What it does: Displays hierarchical data as nested rectangles. Each rectangle's area is proportional to its aggregated value. Color intensity shows relative magnitude within the tree.
How to use:
- Drag a categorical field (e.g., Region, Category) to COLS
- Drag a numeric field (e.g., Sales, Revenue) to ROWS
- Select 🌳 Treemap from the chart type dropdown
- Click Render or press Alt+R
- Larger rectangles = larger values. Labels show category name and value.
When to use: When you have many categories and want to show composition. Better than pie charts for 10+ categories. Ideal for file sizes, market share, budget allocation.
What it does: Multi-level radial chart showing parent-child hierarchy. Inner ring = parent categories, outer ring = children.
How to use:
- Drag a parent dimension to COLS (e.g., Region)
- Drag a measure to ROWS (e.g., Sales)
- Optionally drag a child dimension to Color By mark (e.g., Category)
- Select ☀ Sunburst and render
When to use: Organization structures, multi-level category breakdowns, file directory sizes.
What it does: Shows how values flow from source categories to target categories. Line thickness represents flow volume.
How to use:
- Drag the source dimension to COLS (e.g., Region)
- Drag the target dimension to Color By mark (e.g., Customer Segment)
- Drag the value measure to ROWS (e.g., Sales)
- Select 🔀 Sankey Flow and render
When to use: Customer journey mapping, budget allocation flows, migration patterns, conversion funnels with multiple paths.
What it does: Every numeric field becomes a vertical axis. Each data row is drawn as a line connecting its values across all axes. Reveals multi-dimensional patterns.
How to use:
- Upload a dataset with 2+ numeric fields
- Select ═ Parallel Coords and render
- No shelf configuration needed — all numeric fields are used automatically
- Up to 8 axes and 500 rows are displayed
When to use: Multi-variable comparison, cluster identification, outlier detection, quality control analysis.
What it does: Enhanced scatter plot where a third variable controls bubble size.
How to use:
- Drag a numeric field to COLS (X axis)
- Drag a numeric field to ROWS (Y axis)
- Drag a third numeric field to Size By mark (bubble diameter)
- Optionally drag a dimension to Color By for category coloring
- Select ⚪ Bubble Chart and render
When to use: Revenue vs Profit with Deal Count as size. Population vs GDP with Area as size.
What it does: Polar area chart where each sector's radius represents the value magnitude. Invented by Florence Nightingale.
How to use:
- Drag a dimension to COLS (e.g., Month)
- Drag a measure to ROWS (e.g., Sales)
- Select 🌹 Nightingale Rose and render
When to use: Cyclical data (months, hours, days of week). Better than pie charts for comparing absolute magnitudes because area differences are more visually apparent.
What it does: Automatically bins a numeric field into 15 equal-width ranges and shows the frequency count in each bin.
How to use:
- Drag a numeric field to ROWS (e.g., Salary, Score, Age)
- Select 📊 Histogram and render
- No COLS field needed — bins are created automatically
When to use: Understanding data distribution. Is it normal? Skewed? Bimodal? Identifying outlier ranges. Essential pre-analysis step before statistical modelling.
What it does: Compact KPI chart showing actual vs target with qualitative range bands in the background.
How to use:
- Drag a dimension to COLS (e.g., Department)
- Drag a measure to ROWS (e.g., Revenue)
- Enter a target value in the Goal / Target Line panel on the right
- Select ▰ Bullet Chart and render
- The colored bar = actual value, the marker line = target, background bands = quality ranges
When to use: Replaces gauges in dense dashboard layouts. Sales quotas, budget tracking, KPI scoreboards.
What it does: Replicates Tableau's Story feature. Capture worksheet charts as numbered story points with narrative captions. Navigate between points to present a sequential data narrative.
How to use:
- Click the 📖 Story tab
- Click ＋ Add Point to create a story point
- Go to the Worksheet tab, build a chart
- Return to Story tab and click 📷 Capture to snapshot the chart
- Edit the title and caption (they are contenteditable)
- Add more story points and repeat
- Click 💾 Export Story to download as a standalone HTML presentation
When to use: Board presentations, classroom teaching, client reporting, data journalism, portfolio demonstrations.
What it does: Algorithmic data interpretation engine that analyses your current chart and generates 8 structured insights covering: dataset overview, dominant category, lowest performer, trend direction, variability, distribution shape, concentration analysis, and actionable recommendations.
How to use:
- Build a chart in the Worksheet tab
- Click Explain Data in the menu strip, or open the modal directly
- Click Analyse — insights appear immediately
No AI API is used. All insights are computed from mathematical analysis: mean, standard deviation, coefficient of variation, skewness, linear regression slope, and concentration ratios.
What it does: Full ordinary least-squares (OLS) linear regression between two numeric fields. Results include the regression equation, R² (coefficient of determination), Pearson r, slope, intercept, standard error, and plain-English interpretation.
How to use:
- Click Regression in the menu strip
- Select X (independent) and Y (dependent) numeric fields
- Click Run Regression
- Results table shows all metrics with interpretation
When to use: Before building ML models, understanding variable relationships, forecasting, validating hypotheses.
What it does: Unsupervised machine learning algorithm that groups data points into K clusters based on similarity across two numeric fields. Pure JavaScript implementation — no external library.
How to use:
- Click Clustering in the menu strip
- Select Field 1 and Field 2 (numeric)
- Set K (number of clusters, 2-8)
- Click Run Clustering
- A new _Cluster field is added to your data
- Use Scatter chart with Color By = _Cluster to visualize
When to use: Customer segmentation, anomaly detection, market analysis, grouping students by performance patterns.
What it does: Unified export hub with 9 formats in a visual grid.
| Format | Description |
|---|---|
| PNG Image | High-resolution chart (2x pixel density) |
| SVG Vector | Scalable vector for print publications |
| Data CSV | Currently filtered dataset |
| HTML Report | Standalone analytics report |
| Workbook JSON | Full workspace state (all sheets, data, settings) |
| Print / PDF | Browser print dialog |
| Pivot CSV | Cross-tabulation export |
| Stats CSV | Descriptive statistics summary |
| Dictionary CSV | Field metadata profile |
How to use: Click Export Center in the menu strip. Click any export card.
What it does: Simulates enterprise data governance by restricting which rows are visible in the workspace based on a field-value rule. The original data is preserved and can be fully restored.
How to use:
- Click RLS in the menu strip
- Select a field (e.g., Region) and an allowed value (e.g., "West")
- Click Apply RLS — only matching rows are visible
- All charts, statistics, and exports reflect the restricted data
- Click Clear RLS to restore the full dataset
When to use: Training environments, demonstrating data governance concepts, simulating role-based access, showing clients how RLS works before implementing on Tableau Server.
What it does: Enterprise dashboards support 1, 2, 3, or 4 column grid layouts. The 4-column layout enables dense KPI displays with maximum information density.
How to use: In the Dashboard tab, click ⊞⊞ 4 in the layout selector.
What it does: Exports the current chart as an SVG file — scalable to any size without pixelation.
How to use: Open the Export Center, click SVG Vector, or call exportChartSVG().
| Component | Technology | Cost |
|---|---|---|
| Charting | Apache ECharts 5.4.3 | Free |
| CSV Parsing | PapaParse 5.4.1 | Free |
| UI | Vanilla HTML5 + CSS3 + ES6 JS | Free |
| Fonts | Google Fonts (Sora + DM Mono) | Free |
| Hosting | GitHub Pages / Netlify / Cloudflare Pages | Free |
| Build Tools | None | Free |
| Backend | None | Free |
| Database | None | Free |
| AI/ML API | None | Free |
| Monthly cost | ₦0 / $0 |
Visit the deployed URL in any browser. No login. No sign-up.
- Download
index.html - Double-click to open in any browser
- Works fully offline after first load
git clone https://github.com/cssadewale/tableau-stimulator.git
cd tableau-stimulator
open index.html
# No npm. No build. No config.enterprise/
├── index.html ← The entire application (~310KB)
├── README.md ← This documentation
├── LICENSE.txt ← MIT License
├── CHANGELOG.md ← Full version history
├── CONTRIBUTING.md ← Architecture + contribution guide
├── DEPLOYMENT.md ← 7+ deployment methods
├── SYSTEM_FEATURE_GUIDE.md ← Detailed feature reference
├── SAMPLE_DATA.md ← 5 ready-to-use CSV datasets
├── SECURITY.md ← Data privacy policy
├── CODE_OF_CONDUCT.md ← Community standards
├── QUICK_START.md ← 10-step quickstart
├── sample-sales.csv ← Sample dataset
├── bug_report.md ← Bug report template
├── feature_request.md ← Feature request template
└── nojekyll.txt ← GitHub Pages config
Data Scientist · EdTech Builder · Virtual Tutor · AI-Augmented Solutions Developer
Lagos, Nigeria 🇳🇬
| Platform | Link |
|---|---|
| linkedin.com/in/adewalesamsonadeagbo | |
| 🐙 GitHub | github.com/cssadewale |
| 🌐 Portfolio | cssadewale.pages.dev |
| 🏢 HMG Concepts | hmgconcepts.pages.dev |
| 🎓 HMG Academy | hmgacademy.pages.dev |
| hmgconcepts@gmail.com | |
| +234 810 086 6322 |
MIT License — Copyright (c) 2025-2026 Adewale Samson Adeagbo
Built with clarity of thought · Powered by free tools · Made in Nigeria 🇳🇬
Enterprise-grade analytics without the enterprise price tag.
🌐 Portfolio · 🏢 HMG Concepts · 🎓 HMG Academy
© 2025-2026 Adewale Samson Adeagbo · MIT License