LiteBI Studio

Local-first BI and reporting for privacy-sensitive analytics.

LiteBI Studio is a browser-based workspace for importing, modeling, analyzing, and presenting data without a backend.

It combines Excel import, SQL-based analysis, configurable widgets, dashboards, and report exports in a zero-backend architecture built on SQLite WASM. Your data stays on your machine. No telemetry, no server component, no external data calls during normal usage.

Live Demo | Getting Started | Wiki | Example: Cherit IT Invoice Control

Why LiteBI Studio?

• Local-first by design: data is processed and stored in the browser with SQLite WASM + OPFS.
• No backend required: the app can be hosted statically, including on GitHub Pages.
• Built for controlled environments: suitable for IT controlling, internal reporting, demos, and privacy-sensitive analysis.
• End-to-end workflow in one tool: import, inspect, query, visualize, assemble dashboards, and export reports.
• Flexible data model: works with generic relational structures instead of forcing one business schema.

Use Cases

• IT controlling: analyze invoices, budgets, vendors, cost centers, and operational KPIs locally.
• Internal reporting: build dashboards and export management-ready report packs without standing up backend infrastructure.
• Proof of concept work: validate data models, SQL logic, and reporting flows quickly with a static deployment.
• Regulated or privacy-sensitive scenarios: keep source files and derived datasets on-device.
• Demo and training environments: load prepared examples and walk through realistic end-to-end workflows.

What You Can Do

Analyze Data

• Import Excel data with schema-aware helper flows.
• Inspect tables and views directly in the browser.
• Maintain optional schema documentation for tables, views, columns, and relationships.
• Validate, clean up, export, and import schema metadata without exposing row-level data.
• Build SQL statements in a dedicated SQL editor and preview results immediately.
• Use reusable SQL statements as the basis for widgets and dashboards.

Build Visuals

• Create widgets for tables, KPI tiles, bar/line/area/pie/radar/scatter charts, gauges, pivot tables, and rich text content.
• Configure axes, series, labels, colors, thresholds, and widget descriptions.
• Assemble multiple widgets into dashboards with drag-and-drop layout management.

Package Results

• Build multi-page report packs from dashboards and widgets.
• Export outputs as PDF, image, HTML, JSON, and PPT where supported.
• Use example datasets and guided flows to evaluate the app quickly.

Stay Local and Secure

• Keep data on-device with no mandatory cloud dependency.
• Use app lock protection and encrypted backups.
• Benefit from CSP hardening and a zero-telemetry operating model.

Typical Workflow

1. Import an Excel file in Data Management.
2. Optionally enrich the schema with semantic documentation in Structure & Schema.
3. Explore the loaded tables in Tables.
4. Create or refine queries in SQL Workspace.
5. Turn query results into visuals in Widgets.
6. Arrange widgets into a dashboard.
7. Export a report pack or share results as a local artifact.

Product Tour

Data import and preparation

SQL analysis workspace

Widget and dashboard creation

Try It Quickly

Live Demo

Open the hosted version:

• https://hrmnns.github.io/litebistudio/

Fastest evaluation path:

1. Open the app.
2. Go to Data Management.
3. Import an Excel file or restore the prepared example backup.

Detailed walkthroughs:

• Getting Started
• Example: Cherit IT Invoice Control
• Examples

Privacy note:

• Your data stays local in your browser.
• Normal app usage does not upload your datasets to an external server.

Local Development

Prerequisites

• Node.js 20.x or later
• npm

Install and Run

git clone https://github.com/hrmnns/litebistudio.git
cd litebistudio
npm install
npm run dev

Optional once per clone:

npm run hooks:install

This activates the repository git hooks from .githooks/ so build and test run automatically on push.

Build

npm run build

Local Quality Gates

npm run lint
npm run check:i18n
npm run check:encoding
npm run build
npm run test

Architecture Overview

LiteBI Studio follows a local analytics pipeline:

1. Sources Excel files and local example datasets enter the app through browser-based import flows.
2. Ingest Data is read, mapped, and validated before being persisted.
3. Storage SQLite WASM stores tables, views, and derived structures in browser storage.
4. Analytics SQL statements, saved queries, and widget configurations build reusable analysis layers.
5. UI Widgets, dashboards, and report packs present the results.

Important technical characteristics:

• Frontend: React 19 + TypeScript + Vite
• Styling: Tailwind CSS
• Database: SQLite WASM + OPFS
• Charts: Recharts
• i18n: i18next (DE / EN)
• Export stack: html2canvas + jsPDF

Documentation

The repository wiki source lives in docs/wiki/.

Recommended starting points:

• Wiki Home
• Getting Started
• Examples
• Architecture
• Page: Data Management
• Page: SQL Workspace
• Page: Widgets
• Page: Dashboard
• Security and Privacy

The GitHub Wiki is synchronized from the repository through .github/workflows/wiki-sync.yml.

Project Structure

• src/app/ UI views, widgets, layout, and page-specific logic
• src/components/ shared UI building blocks
• src/hooks/ reusable hooks for async state, local storage, export, and app behavior
• src/lib/ repositories, DB integration, security utilities, app state, and infrastructure
• src/locales/ translation files for German and English
• src/datasets/ schema and dataset-related SQL
• docs/wiki/ user and maintainer documentation
• scripts/ repository maintenance and validation scripts

Deployment

LiteBI Studio is optimized for static hosting.

• npm run build produces the production bundle in dist/.
• The app uses coi-serviceworker.js so SharedArrayBuffer/OPFS features can work on GitHub Pages without custom server headers.
• If OPFS is unavailable, the app falls back gracefully to in-memory database behavior.

Security and Privacy

• No external tracking or telemetry
• No mandatory server component
• Data sovereignty through local browser storage and local file import/export
• CSP restrictions to limit unauthorized outbound connections
• App lock with salted protection
• AES-GCM encrypted backups

CI, Releases, and Changelog

• CI workflow: .github/workflows/ci.yml
• Wiki sync workflow: .github/workflows/wiki-sync.yml
• Release history: CHANGELOG.md
• Versioning: Semantic Versioning

Recommended branch protection:

• require CI / quality-gates (pull_request) before merging into main

What LiteBI Studio Is Not

• Not a hosted SaaS BI platform
• Not a multi-user server application
• Not dependent on a cloud warehouse or external API backend

That tradeoff is intentional: LiteBI Studio prioritizes local control, portability, and privacy over centralized orchestration.

---

Built for local analytics, data sovereignty, and fast insight loops.