Datameer Blog post

2016 Predictions for the Big Data Market

by on Dec 07, 2015

Throughout the year I’ve weighed in with 2-3 minute videos on key trends and news in the big data market for our Big Data & Brews Perspective series. But it’s December now, which means its time to think even bigger. What’s 2016 have in store for us in the Big Data space and beyond? I’ve outlined my high-level predictions below, and talked about my top 3 in this week’s 2016 Perspectives video (embedded below). But if you want to go even deeper, be sure to register now to join me and ZDNet Big Data writer and our Senior Director of Market Intelligence and Strategies, Andrew Brust, for a lively discussion January 21st. Between the two of us, who have been known to have a strong opinion or two, you’ll walk away with enough insight on why we think these predictions make sense – and we hope you’ll join in the conversation too.

    1. IoT moves from hype to substance
      The Internet of Things has already emerged as the next mega-trend but in 2016, it will excel beyond just hype. We will see companies actively change their strategy and infrastructure to harness the power and insight of IoT technologies and data.
    2. Cloud analytics becomes a game changer
      Right now, a few cloud-only Hadoop players exist, and other vendors offer rather distinct on-prem and cloud editions of their products. In 2016, as companies recognize the advantage of side-stepping Hadoop hardware requirements, which become outdated every 18 months, cloud adoption will surge. Vendors, particularly distributors, will pivot their offerings in order to keep up with demand.
    3. Streaming data mainstreams, and gets easier
      The desire to gather data – and analyze it – in real-time will grow immensely in 2016, driven by Internet of Things (IoT) applications and the plain old human tendency toward instant gratification. Mitigating the complexities of mashing up real-time and historical data will become a focal point – pointing toward technologies like Kafka and others.
    4. Operational analytics on the upswing
      Customer analytics is traditionally considered the primary use case for big data analytics. But, as companies better understand their customer base, use cases will move from external to internal – making operational analytics the main use case.
    5. Best-of-breed loses luster
      When a technology category is new, various companies emerge with individual products that aim to provide a solution for a portion of the space. This leaves customers buying a number of tools and trying to learn how to use them together. Eventually, that just won’t do, and customers tend towards an integrated stack of products – or a widely-scoped product – from a single vendor. 2016 will mark the beginning of that transition for Big Data products.
    6. Industry consolidation reaches critical mass
      A number of acquisitions have taken place over the last two years as larger organizations try to fill holes in their offerings, shrinking the number of pure-play, standalone Big Data vendors. That will continue this year and likely reach critical mass.

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