Big Data's Priorities: Streaming Analytics, Self-Service

Businesses are taking the next step with big data technology in 2016 with plans to implement streaming analytics and self-service, as they work to embed big data insights directly into business applications and software.

Jessica Davis, Senior Editor

March 17, 2016

4 Min Read
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Streaming analytics, self-service options, and embedding big data insights into the applications that drive the business are the new priorities for organizations as they evaluate their big data strategies.

That's according to a new TechRadar report from Forrester Research that looks at the state of big data in businesses today.

Enterprise organizations have reached a new stage in big data adoption, and in 2016 they will be looking to embed the technology into the applications that power their businesses via integration and APIs.

The priorities for this year mark a change from organizations' comfort level just three years ago with big data technologies. In 2013, customers were still trying to grapple with branching out from their traditional data technologies to those that could encompass big data. But in those few years, organizations have gained enough confidence to want more. And at the same time the technology has advanced.

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"Forrester has seen an explosion in client adoption of big data since we first wrote about it in 2011," wrote Brian Hopkins, Forrester Research VP and principal analyst serving enterprise architecture professionals, in the TechRadar report. "For example, the number of firms implementing streaming analytics, a key leading-edge big data technology, more than doubled between 2012 and 2015."

Streaming Analytics

Forrester has identified key vendors and technology for streaming analytics as Apache Spark Streaming, Apache Storm, Data Torrent, IBM, Informatica, SAP, Software AG, SQLstream, Striim (WebAction), TIBCO, and Vitria.

The analyst firm defines stream analytics software as technology that "can filter, aggregate, enrich, and analyze a high throughput of data from multiple disparate live data sources and in any data format to identify simple and complex patterns to visualize business in real-time, detect urgent situations, and automate immediate actions."

The rise of streaming technologies such as Apache Spark highlights one of today's challenges for enterprises -- the need to process and analyze data in real-time.

Enterprise Data Management and Big Data

With that in mind, Forrester noted that many of its clients are at a crossroads with their data management and big data programs, looking to invest in technology for real-time data processing and user and customer self service, but not knowing which options to choose amid a crowded field of options from open source and commercial vendors.

And organizations are planning to invest.

Forrester noted 61% of North American and European companies had implemented or planned to implement big data by the end of 2016, according to its Global Business Technographics Data And Analytics Survey, 2015, which polled 3,005 business and technology decision makers at companies with 100 or more employees in the US, Australia, Brazil, Canada, China, France, Germany, India, New Zealand, and the UK.

Advanced Analytics, In-Memory, And Data Preparation Tools

Newer enterprise goals for big data mean that technologies such as advanced analytics conducted in-memory and data preparation tools are in high demand, according to Forrester.

Forrester looked at about 20 different technology categories that touch big data, spoke with multiple vendors and experts in the field, and found that five specific technology categories ranked the highest in terms of customer interest. Those categories are data integration, data services and APIs, in-memory computing, data preparation and discovery, advanced analytics, and monitoring and administration. All these categories have something in common. They enable the integration of insights into "the fabric of business," the report notes.

"To keep pushing revenue growth and digital customer experience transformation, big data technology is expanding its scope," wrote Hopkins. "It must also address the scale, speed, and integration requirements necessary to embed insights into the very fabric of next-generation, insights-driven businesses."

About the Author(s)

Jessica Davis

Senior Editor

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: @jessicadavis.

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