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IBM expands portfolio with new products and a developer marketplace
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February 12, 2016 Blogs big data

This article was originally published by techrepublic.com and can be viewed in full here

IBM announced four new cloud products on Thursday as well as an expansion of its current products on Bluemix, signifying a shift in the company’s overall strategy.

On Thursday, IBM announced that it was expanding the big data services available on its cloud platform, Bluemix. More than 25 services will now be available on the platform, including four newly-announced products, with the goal of helping “developers and data scientists build and move data into the cloud.”

IBM already has a few tools available for processes such as data preparation and modeling but, as part of Thursday’s announcement, they introduced the following four cloud data services:

  • IBM Compose Enterprise is a platform to help developers build web applications more efficiently by leveraging open source databases on dedicated cloud servers.
  • IBM Graph is a graph database service, built on Apache TinkerPop, an open source graph technology stack. Developers using IBM Graph can add features like IoT capabilities, network analysis, and more to existing apps
  • IBM Predictive Analytics: This service allows developers to add machine learning capabilities to their apps, without needing a data scientist to do so. The machine learning models are available through a library that developers can access.
  • IBM Analytics Exchange: Developers get access to a public catalog of datasets that they can integrate into their applications, or use for another instance of data analysis.

Adam Kocoloski, CTO of the IBM analytics platform and cloud data services, said that whether your company is an enterprise giant or a brand new startup, embracing data is unavoidable. But, that’s always easier said than done.

“Even preparing massive and varied forms of data so they’re usable or leveraging the right tools to discover insights and act on them can be very difficult for businesses,” Kocoloski said. “The companies that find a way to enable collaboration using an integrated set of data tools and technologies on a single platform are the ones who will get data-driven strategies to market faster and realize significant advantages.”

These hybrid cloud services are based on open source technologies and are meant to be deployed across multiple cloud providers. Kocoloski said that was intentional on IBM’s part, as they have noticed an increase in businesses wanting open source technologies with a cloud delivery model for the flexibility it brings.

“IBM’s open approach means that any member of a data team can add or remove services at any time to best suit immediate and long-term needs of their business,” Kocoloski said.

And, a big part of that emphasis on open source—and IBM’s big data strategy in general—is the support of Apache Spark. Kocoloski went as far as to say that Spark is “becoming the de facto operating system for big data,” noting IBM’s many contributions to the project, including their goal of educating more than one million data scientists and engineers on the technology.

Forrester’s Michele Goetz said the announcement is a key next step for IBM, as the company continues its transition to big data and the cloud. But, it’s one of many investments, partnerships, and acquisitions that they have recently made in the space.

US automaker Ford recently partnered with Big Blue to develop a platform to analyze vehicular data. Additionally, IBM’s recent earnings showed a distinct shift toward the cloud as a focus, alongside its cognitive computing platform Watson, while its legacy offerings in server hardware and enterprise software contracted.

However, IBM still faces heavy competition from the likes of the big three cloud providers: AWS, Microsoft Azure, and Google Cloud Platform.

“IBM’s primary competition for now will be from Microsoft as Azure is gaining traction from its easy to use environment for machine learning, mature API marketplace, and breadth of services offered, linking front office applications with back office infrastructure to get insights into action in real-time for app dev teams,” Goetz said.

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