Managing Big Data with Google Cloud Datalab

The Google Cloud Datalab?is Google’s answer to big data exploration, analysis and visualization.

All cloud service providers are competing intensely to close the loop of offerings in the realm of big data services that includes exploration, transformation, analysis, and visualization services. In an earlier post, I mentioned the announcement of QuickSight, the data visualization platform from the Amazon Web Services team that now makes the platform an end-to-end provider of cloud-based real-time data stream analytics and visualization services, competing neck and neck with Microsoft Azure’s Analytics Platform System. Guess what, Google is not far behind either!

Last week it announced the availability of Cloud Datalab, Google Cloud’s platform for data exploration, analysis and visualization. The timing of this beta release couldn’t have been sweeter as it comes closely on the heels of Google announcement of the open sourcing of its machine learning platform TensorFlow.

Datalab is extremely interactive and provides for an interactive notebook environment where you can store your analysis as notebooks and then publish and share your insights with the world. As a developer you can go further to develop, test, and deploy data processing pipelines. Support for BigQuery?is most obvious. You can seamlessly write code in Python, SQL, and BigQuery UDF constructs to build and test your pipeline. Underlying it leverages Jupyter, a powerful web-based notebook platform for sharing documents containing live code. This becomes particularly useful for storing machine learning and statistical models. You can even reuse existing Jupyter notebooks.

To start using Datalab, you need to first register your application for Google Compute Engine.

If you don’t have an account, you can sign-up for a free trial with $300 credit. If there are no existing projects in your developer console, a default “My Project” is created.

Once your billing is activated, you can start deploying your Cloud Datalab as an App Engine application.

As far as pricing is concerned, you only pay for the use of underlying cloud resources by the App Engine such as BigQuery and Storage. Competition is sure to get hotter with this release, and only time will pronounce the winner!

Share the Post:
Share on facebook
Share on twitter
Share on linkedin


The Latest

homes in the real estate industry

Exploring the Latest Tech Trends Impacting the Real Estate Industry

The real estate industry is changing thanks to the newest technological advancements. These new developments — from blockchain and AI to virtual reality and 3D printing — are poised to change how we buy and sell homes. Real estate brokers, buyers, sellers, wholesale real estate professionals, fix and flippers, and beyond may

man on floor with data

DevX Quick Guide to Data Ingestion

One of the biggest trends of the 21st century is the massive surge in internet usage. With major innovations such as smart technology, social media, and online shopping sites, the internet has become an essential part of everyday life for a large portion of the population. Due to this internet

payment via phone

7 Ways Technology Has Changed Traditional Payments

In today’s digital world, technology has changed how we make payments. From contactless cards to mobile wallets, it’s now easier to pay for goods and services without carrying cash or using a checkbook. This article will look at seven of the most significant ways technology has transformed traditional payment methods.