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Microsoft Add Even More Features to Azure to Bring Big Data to the Mainstream

byDataconomy News Desk
February 26, 2015
in Articles, News

Microsoft is rolling out new Azure services as a part of the larger strategy to “help more people realize the possibilities of big data.”

Last week, at the  Strata + Hadoop World conference in San Jose, the tech giant claimed to make “big data simpler and more accessible” to the masses, with the following releases:

  1. A preview of Azure HDInsight running on Linux
  2. The general availability of Storm on HDInsight
  3. The general availability of Azure Machine Learning
  4. The availability of Informatica technology on Azure

Azure HDInsight is an Apache Hadoop-based service in the cloud enabling customers to crunch petabytes of all types of data in speed and cost-effectively scaling on demand, as well as programming extensions so developers can use their favorite languages. Customers will now be able to run HDInsight on Ubuntu clusters.

The open source stream analytics platform Storm for Azure HDInsight, enables processing of millions of data events in real time as they occur.

Azure Machine Learning promises to provide advanced analytics for businesses to predict future trends with data.

“In mere hours, developers and data scientists can build and deploy apps to improve customer experiences, predict and prevent system failures, enhance operational efficiencies, uncover new technical insights, or a universe of other benefits,” write T. K. Rengarajan, corporate vice president, Data Platform and Joseph Sirosh, corporate vice president, Machine Learning, for the blog post making the announcement.

More details about HDInsight are available on this blog.

Azure Marketplace has Informatica joining other partners making its Informatica Cloud agent available in Linux and Windows virtual machines on Azure. Microsoft notes that this “will enable enterprise customers to create data pipelines from both on-premises systems and the cloud to Azure data services such as Azure HDInsight, Azure Machine Learning, Azure Data Factory and others, for management and analysis.”

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(Image credit: Roman Azure by Terratrekking, via Flickr)

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