Cloudera and T-Systems Offer Analytics-as-a-Service

By Robbie Pleasant

It may often seem like everything is being offered 'as-a-service' these days – not that there’s anything wrong with that. After all, it makes it easier for companies to access important tools and services without having to host their own, which saves money, time and energy.

Now, Cloudera is offering Analytics-as-a-Service through T-Systems, which will be provided to its customers through its cloud infrastructure.

Together, the two companies will create and deliver services that help customers analyze and gain value from their data, brought to them from the cloud. It will use Cloudera Enterprise RTQ on a T-Systems cloud, made available immediately to T-Systems’ European customers, and to its customers outside of Europe at a later time.

The data management infrastructure layer is provided by Cloudera’s Impala RTQ. This layer will enable native data integration, visualization and analysis, so customers accessing it can analyze and manage their data effectively and quickly.

"Our customers don't want to have to worry about the hardware and software for big data,” said Christian Wirth of T-Systems. “They don't want technology, just a reliable service. We can offer precisely this – which is what makes our new offer with Cloudera so special."

There’s no doubt that data analytics and management is important to businesses. It can help determine what’s working and what isn’t – the best way to adjust a product, pitch, sales, advertisements, or anything of the sort – and basically give a thumbs-up or thumbs-down to business as usual.

Still, many companies find that seeking and purchasing the proper products for that can be expensive and unwieldy, so offering it through the cloud can help them greatly. They can access the services they need affordably, and it’s scalable to their needs.

Together, Cloudera and T-Systems are making it possible for many more businesses to get the analysis they need to better run and manage pretty much everything, gaining the most value from their data at the most efficient pace.

Edited by Braden Becker

MSPToday Contributor

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