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21 data and analytics trends that will dominate 2016

Thor Olavsrud | Jan. 19, 2016
Five industry insiders predict the trends that will shape the big data and analytics market in 2016.

data analytics trends

Along with social, mobile and cloud, analytics and associated data technologies have earned a place as one of the core disruptors of the digital age. 2015 saw big data initiatives moving from test to production and a strong push to leverage new data technologies to power business intelligence. As 2016 gets underway, five insiders share their predictions for what 2016 holds in store for the data and analytics space.

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks, predicts the following trends will dominate data and analytics in 2016:

  • Internet of Anything. In 2016, businesses will look at deriving value from all data, Gnau says. "It's not just the Internet of Things but rather Internet of Anything that can provide insights," he says. "Getting value from data extends beyond devices, sensors and machines and includes all data including that produced by server logs, geo location and data from the Internet."
  • Data at the jagged edge. Businesses must look beyond the edge of their data centers all the way out to the jagged edge of data, Gnau says. He notes that data flows now originate outside the data from many devices, sensors and servers on — for example, an oil rig in the ocean or a satellite in space. There is a huge opportunity to manage the security perimeter as well as to provide complete data provenance across the ecosystem. Gnau says IoAT creates a new paradigm that requires new thinking and new data management systems, and these solutions will mature and permeate the enterprise in 2016.
  • Data in motion platform.The industry will see the evolution of data in motion platforms in 2016. "There is a need for a higher-level platform to handle the many device protocols and bring all of the data flows into Hadoop," Gnau says. "The platform needs to facilitate communications in multiple protocol languages. There combination of data in motion and data at rest is a big opportunity for the year."
  • Big data made easy. There is a market need to simplify big data technologies, and opportunities for this exist at all levels: technical, consumption and so on. Gnau says that in 2016 there will be significant progress toward simplification. "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward," he says. "Things like a single integrated developer experience or a reduced number of settings or profiles will start to appear across the board."
  • Hadoop for mission critical workloads. In 2016, Hadoop will be used to deliver more mission critical workloads — beyond the "web scale" companies, Gnau predicts. "While companies like Yahoo, Spotify and TrueCar all have built businesses which significantly leverage Hadoop, we will see Hadoop used by more traditional enterprises to extract valuable insights from the vast quantity of data under management and deliver net new mission critical analytic applications which simply weren't possible without Hadoop," he says.

 

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