Data-Centric Notebooks

Vizier is a notebook that puts your data front-and-center.

Whether you prefer to use spreadsheets, notebook scripting, or databases, Vizier makes it easy to to explore the data to find out what you have, validate that the data makes sense, and transform it to fix bugs and mold it into a form your tools can use.

There is a lot of hate for some popular notebooks. Unlike most popular notebooks, Vizier is multi-lingual and multi-modal, letting you edit your data through the best interface for what you're trying to do. On top of that, it tracks provenance of your data and automatically versions your workflows. Vizier also uses dependency analysis to make sure you're never looking at stale outputs.

Screenshots     Video Demo     Docs     Install

Run with Bootstrap

(Requires Java JDK 8)

# Install Vizier
$> wget
$> chmod +x vizier
$> sudo mv vizier /usr/local/bin

# Run Vizier
$> vizier

Detailed Instructions / FAQ

Run With Docker

(Requires Docker)

$> docker run \
          -p 5000:5000 \
          --name vizier \

(Connect at http://localhost:5000)

A truly multi-lingual notebook.

Seamlessly switch between languages within the same notebook. Vizier currently supports Python, SQL, and Spark. Alternatively, add one of Vizier's pre-canned data widgets to plot data or repair errors with only a few clicks.

Notebook or Spreadsheet. Why choose?

For small fixes, you can directly edit your data frames through Vizier's spreadsheet mode. Changes in spreadsheet mode are immediately reflected back into the notebook.

The power of provenance

Vizier tracks where your data comes from and what's happened to it. This means Vizier knows which cells depend on which other cells. When you make a change, Vizier re-runs exactly those cells that are needed to make sure you're not looking at stale data. Vizier also tracks possible errors in your data tagging your data values when something goes wrong.

Versioning without the sweat

Everything you do in Vizier is versioned. Made a mistake? No problem, just go back to an earlier version. Share snapshots of your workflow with collaborators, or branch your workflow to try something different.

Video Tour


Vizier is supported by NSF Awards ACI-1640864 and IIS-1750460.


The Team


    Data Debugging and Exploration with Vizier   SIGMOD 2019 (Demo)   ( paper )
    Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers   SIGMOD 2019   ( paper )
    Adaptive Schema Databases   CIDR 2017   ( paper )
    Communicating Data Quality in On-Demand Curation   QDB 2016   ( paper )
    The Exception That Improves The Rule   HILDA 2016   ( paper )
    Provenance-aware Versioned Dataworkspaces   TaPP 2016   ( paper )
    Lenses: An On-Demand Approach to ETL   VLDB   ( paper )