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Five Reasons Machine Learning Is Moving to the Cloud

Thursday, 7 May, 2015 - 15:45

 

Amazon Web Services turned a lot of heads recently when it launched a machine learning platform aimed at making predictive analytics applications easy to build and run, joining cloud juggernauts Microsoft and Google with similar ML offerings. It turns out the cloud is very well-suited for this critical type of big data workload. Here are five reasons why.

 

Google Opens Cloud Dataflow To All Developers, Launches European Zone For BigQuery

Tuesday, 21 April, 2015 - 12:30

 

Google launched a couple of updates to its cloud-based big data products at the Hadoop Summit in Brussels on 16 April. These included the launch of the open beta of Cloud Dataflow, Google’s new service for processing huge amounts of data, as well as an update to BigQuery, which will make the company’s bid data database service available in Google’s European data centers and introduces row-level permissions.

 

ARTIST - Advanced software-based seRvice provisioning and migraTIon of legacy Software

Focus Area

For software companies, cloud computing offers a modern world of business opportunity, allowing them to provide their application not only as a product but as a service. Thus, they will enjoy, among other advantages, of agility and efficiency.

Migrating software to cloud infrastructure may be sufficient much of the time. But residing in the cloud is not enough to make an application fully scalable, elastic and ‘cloudy’. The software code itself must be modernized if maximum performance and efficiency are required.

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