The problem
Business users frequently receive CSV and Excel files but lack the time or analytical expertise to manually profile the data, explore dozens of field combinations, identify unusual behaviour and build an executive-ready report.
Flagship Data Product · Live
Azhan Data Studio
A self-service automated data intelligence product that turns CSV and Excel files into semantic profiles, ranked insights, visual discoveries, data-quality evidence and presentation-ready reports.
CSV + XLSXMulti-sheet workbooksDeterministic analyticsNo LLM required
01 · The Challenge
Most people have data. Fewer know what to analyse first.
Traditional BI tools are powerful, but they usually require the user to know which fields matter, what questions to ask, which visual to choose and how to interpret the result. Azhan Data Studio was designed around a different starting point: “What should I know about this dataset?”
The product idea
Upload structured data once. The platform understands the fields, discovers statistically meaningful signals, ranks what deserves attention, chooses useful visuals and packages the results for sharing.
02 · How It Works
From raw file to decision-ready briefing.
The analytics pipeline is deliberately separated into clear layers so every visible finding can be traced back to calculated evidence.
Step 1UploadCSV or Excel, with worksheet selection for multi-sheet workbooks.
Step 2UnderstandDetect technical types, semantic roles and field quality.
Step 3DiscoverFind trends, relationships, group differences, anomalies and distributions.
Step 4RankScore findings using impact, confidence, unusualness, coverage and relevance.
Step 5VisualiseSelect suitable charts based on the type of analytical evidence.
Step 6ReportProduce branded PDF-ready output and downloadable insight registers.
03 · Core Capabilities
A general-purpose analytics engine, not an industry template.
The platform is designed to work across structured datasets without assuming the file contains sales, HR, inventory, automotive or any other specific business domain.
Semantic field detection
Recognises identifiers, measures, categories, time fields, percentages, binary variables and free text.
Data quality profiling
Surfaces missing values, duplicates, completeness, unusual field behaviour and analysis readiness.
Insight discovery
Analyses trends, correlations, group differences, outcome gaps, anomalies, concentration, skew and variability.
Insight ranking
Prioritises the strongest signals instead of presenting every technically valid observation equally.
Visual discovery
Automatically generates relevant trend, scatter, distribution, category, correlation and quality visuals.
Workbook intelligence
Detects Excel worksheets, previews their shape and lets users choose the sheet they want to analyse.
Report-ready output
Creates a branded analytical report with top findings, charts, quality evidence and an insight register.
Transparent evidence
Every finding carries calculated evidence so the user can see why the engine surfaced it.
04 · Architecture
Analytics first. Interpretation second.
Azhan Data Studio keeps the calculation layer deterministic. Python and Polars profile the data and run statistical discovery modules; the interface then presents those verified results through rankings, charts and reports.
Design principleNo AI assistant or LLM is required to calculate or explain the core analysis. This keeps the product predictable, reproducible and free from per-request AI API costs.
FrontendNext.js + TypeScriptUpload experience, workspaces, charts and report UI.
APIFastAPISecure boundary between the web application and analytics engine.
AnalyticsPython + PolarsProfiling, statistical discovery and evidence generation.
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LogicInsight RankingImpact, confidence, unusualness, coverage and relevance.
OutputVisual DiscoveryAutomatic chart selection based on finding type.
DeliveryNetlify + RailwayPublic Next.js frontend connected to a hosted Python API.
05 · Technology
Built as a real web product.
The project combines front-end product design, backend API engineering and analytical computation rather than relying on a pre-built dashboard framework.
Next.jsReactTypeScriptPythonFastAPIPolarsStatistical AnalysisNetlifyRailwayGitHub
06 · Outcome
What this project demonstrates.
Azhan Data Studio is a portfolio project, but it is also a working public product that brings together several disciplines in one experience.
DataProfiling, statistics, quality analysis, insight discovery and evidence-based ranking.
ProductUser journey design, progressive disclosure, workbook handling and report workflows.
EngineeringNext.js frontend, FastAPI service, Python analytics and cloud deployment.
Live Product
Try Azhan Data Studio.
Upload a CSV or Excel workbook and see the analytics pipeline work on your own structured data.