DataSlicer by datafeta

Explorative Data Analysis For Engineers - No Fancy BI-Dashboards

Open-source OLAP-style data analysis in your browser.
Connect to ClickHouse, Kaggle, or CSV/Parquet files and explore your data interactively.

Open the app → GitHub

Heard of Polaris Formalism?
It's the theoretical foundation of data visualization tools like Tableau™.
DataSlicer implements many of Polaris' core concepts.

What it does

🔌

Connect your data

Works with ClickHouse, Kaggle, CSV and Parquet files. More connectors planned.

🧮

OLAP-style exploration

Drag dimensions and measures to build charts and aggregations without writing SQL.

📊

Build rich visualizations

Create charts, distributions, overlays, and small multiples from the same drag-and-drop exploration flow.

⚡

Fast re-queries

Query results are cached locally using DuckDB WASM in your browser, so interactive exploration stays snappy.

🚀

Billion-row scale

Adaptive sampling, smart binning, and layered caching let you explore datasets with billions of rows seamlessly.

🔓

Open source

AGPL licensed. Self-hostable. No usage tracking, no data leaves your infrastructure.

Features

Bar, line, scatter, area, pie charts
Heatmap, CDF / distribution, Gantt, tick-strip / box-plot
Geo / map charts coming soon
Pivot table coming soon
Faceted views & small multiples
Color, size and shape encodings
Filters with interactive cross-filtering
Linear regression & density overlays
Multi-tab sessions with isolated state
Connect to ClickHouse, CSV, Parquet, Kaggle more to come
DuckDB WASM result cache in the browser
Self-hostable, AGPL licensed

How it works

Connect

Point DataSlicer at your ClickHouse instance, or upload a CSV/Parquet file.

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Explore

Drag fields onto axes, apply filters, chart type auto-detect or manual.

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Iterate

Results cache locally so subsequent queries are near-instant.

Free & open source

DataSlicer is free to use and open source under the AGPL license.
Self-host it, contribute, or just experiment with the hosted version.

View on GitHub →