Google Cloud Datalab Beta
Written by Kay Ewbank   
Wednesday, 02 December 2015

Google has launched a beta of Cloud Datalab, a new data visualization service, that you can use to analyze raw data and to explore, share, and publish reports.

The web-based service that combines elements of Google BigQuery and Google Cloud Storage with data science ecosystems built around IPython, and takes care of the integration between the products.




Cloud Datalab is an interactive tool that you can use to create that explores, transforms, visualizes and processes data in Google Cloud Platform. You can combine code Python, SQL and JavaScript (at least JavaScript for expressing BigQuery User Defined Functions). Datalab also lets you build and test data pipeline for deployment to BigQuery, and create, tune, and deploy Machine Learning models.

Writing about the beta on the Google Cloud Platform blogspot, Greg DeMichellie, Director of Product Management at Google said:

"Datalab provides a ready-to-use, fully setup, secure, multi-user environment integrated with source control for developers and data scientists."

The new tool was announced at the recent Google Cloud Platform Next experience event in Paris. Developers will deploy the service as a Google App Engine application that uses Big Query and Cloud Storage as underlying services. Cloud Datalab is built on Jupyter notebooks. . Jupyter was formerly called iPython, and it uses the concept of a Jupyter Notebook, a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.

Cloud Datalab comes with some pre-installed notebooks to illustrate what you can do, and you can also make use of existing Jupyter packages including statistical and machine learning libraries. The data visualization can use Google Charting or the matplotlib Python library. 




While there are business intelligence tools such as Microsoft PowerBI and Amazon QuickSight, Cloud Datalab looks an interesting alternative, given Google is aiming it specifically at developers rather than end users. It is also avoiding the term BI. Another plus point of Datalab is the fact it is open source and developers who want to extend it can just fork it, or submit pull requests on GitHub.



More Information

Cloud Datalab

Google Cloud Platform Blogspot

Jupyter on GitHub

Related Articles

Jupyter 4.0 Released

Google Cloud Big Data

Amazon Quicksight

IPython 3 Released


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Last Updated ( Tuesday, 01 December 2015 )