Cloud Datalab

An easy-to-use interactive tool for data exploration, analysis, visualization, and machine learning.

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Powerful data exploration

Powerful data exploration

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform, and visualize data and build machine learning models on Google Cloud Platform. It runs on Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Integrated and open source

Cloud Datalab is built on Jupyter (formerly IPython), which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on BigQuery, Cloud Machine Learning Engine, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions).


Whether you're analyzing megabytes or terabytes, Cloud Datalab has you covered. Query terabytes of data in BigQuery, run local analysis on sampled data, and run training jobs on terabytes of data in Cloud Machine Learning Engine seamlessly.

Data management and visualization

Use Cloud Datalab to gain insight from your data. Interactively explore, transform, analyze, and visualize your data using BigQuery, Cloud Storage, and Python.

Machine learning with lifecycle support

Go from data to deployed machine learning (ML) models ready for prediction. Explore data, build, evaluate, and optimize machine learning models using TensorFlow or Cloud Machine Learning Engine.



Cloud Datalab simplifies data processing with Cloud BigQuery, Cloud Machine Learning Engine, Cloud Storage, and Stackdriver Monitoring. Authentication, cloud computation, and source control are taken care of out-of-the-box.

Multi-language support

Cloud Datalab currently supports Python, SQL, and JavaScript (for BigQuery user-defined functions).

Notebook format

Cloud Datalab combines code, documentation, results, and visualizations together in an intuitive notebook format.

Pay-per-use pricing

Only pay for the cloud resources you use: Compute Engine VMs, BigQuery, and any additional resources you decide to use, such as Cloud Storage.

Interactive data visualization

Use Google Charting or matplotlib for easy visualizations.

Machine learning

Supports TensorFlow-based deep ML models in addition to scikit-learn. Scales training and prediction via specialized libraries for Cloud Machine Learning Engine.

IPython support

Datalab is based on Jupyter (formerly IPython) so you can use a large number of existing packages for statistics, machine learning, etc. Learn from published notebooks and swap tips with a vibrant IPython community.

Open source

Developers wishing to extend Datalab can fork and/or submit pull requests on the GitHub hosted project.

Technical resources


Datalab is available at no extra charge. You may incur compute, storage, and other cloud services costs based on usage.

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