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Spark and the crux of differentiation

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Big Data Evangelist, IBM

Apache Spark is open-source at its very marrow. And in theory, vendor differentiation is not supposed to matter in an economy in which open-source technologies are the coin of the realm. Isn’t everything given away for free, with all innovative code contributed right back, royalty-free, to the open-source community? So how does any solution provider differentiate itself in such a market? Indeed, how can anybody make any money at it?

http://www.ibmbigdatahub.com/sites/default/files/sparkdifferentiation_blog.jpgConsidering that open-source technologies have been pervasive in high-tech for more than two decades, by now we all know the multilayered answer to these questions. But after last week’s IBM announcements related to Apache Spark, you may be wondering how a large, multinational solution provider, more than a century old, can be confident that its substantial investment in an open-source technology will deliver healthy returns.

The answer is right up front, in IBM’s multifaceted announcements surrounding Spark. IBM has a long history of joining powerful, innovative open-source projects and making markets by contributing significant technological improvements with supporting business solutions to maximize value. In a nutshell, IBM’s commitment to investing in Spark is deep, broad and long-term, spanning the following principal areas:

  • Adopt Spark throughout IBM: IBM will integrate Spark throughout its revenue-producing solution and service portfolio. IBM will differentiate its Spark offerings by weaving them throughout its analytics, commerce, cloud, Watson, content management and systems solution portfolio. IBM will also provide a subscription-based Apache Spark as a Service offering on Bluemix, as well as expert integrated systems that optimize Spark for Power Systems. IBM will offer Spark consulting services to help clients build and deploy these applications. IBM will provide tools for managing Spark assets within and across servers, data centers and clouds.
     
  • Accelerate research and development investment into Spark: IBM will step up its research and development activities into Spark at its labs and development centers throughout the world. This intellectual property will find its way into IBM’s own solution and service portfolio while also being available for licensing by IBM partners across many industries. Much of this R&D is in the area of machine learning, one of the most pivotal assets in an insight economy powered by data and analytics, cognitive computing and algorithmic decision automation tools.
     
  • Establish a center of excellence for Spark developers: IBM has opened the Spark Technology Center (STC) at its facility in downtown San Francisco to help developers—including IBM developers and developers of IBM partners and clients—foster design-led innovations in applications powered by big data analytics. More broadly, IBM will educate IBMers, partners and customers on Spark through its own professional services organization, through the Big Data University online resource and through strategic partners. In this way, IBM will be triggering a new era of design and innovation in the development of the Spark-infused applications, services, devices and other smart artifacts that are transforming our world.

IBM’s landmark announcements last week might be regarded as “Big Blue validating Spark,” and IBM is fine with such a perception. This technology is well on its way toward pervasiveness, and IBM’s path to differentiating itself going forward in this market will involve working more creatively with its partner ecosystem and customers—as well as ramping up its own internal R&D and product development activities—to continue innovating.

As clients rethink their own business strategies in the era of data and analytics initiatives with Spark in mind, IBM is happy to have broken the ice in the enterprise and is doing its part to accelerate this new technology into the business. In fact, IBM clients are already beginning to do exciting things using Spark. The first movers and those who come to Spark later will become increasingly skilled at using Spark to complement descriptive analysis—such as performance-management dashboards—using machine-learning applications that sense their surroundings and drive predictive and prescriptive actions across all business processes, both internal and customer-facing.

This means that by using Spark, IBM’s clients can benefit from applications that deploy insights at the front lines of their business with exponentially increasing speed. The modern crux of competitive differentiation rides on the power of data, the simplicity of design and the speed of innovation. Data’s true value comes from its ability to deliver the right business outcomes with zero lag time. IBM is happy when customers can use its offerings to differentiate themselves on that basis.

You can learn more about IBM’s deep commitment to Spark and engagement with IBM’s partner ecosystem by visiting the following online resources: 

Also, please sign up for IBM’s forthcoming Apache Spark as a Service on Bluemix.