2016 Big Analytics Predictions Roundup

Before publishing my own predictions for 2016 later this week, I thought it would be fun to round up published predictions on analytics and Big Data.  Looking through this list, I see a few patterns:

— Streaming is hot.  Analysts do not seem to understand distinctions between streaming data, streaming analytics and real-time decisioning.

— “Data Science” continues to be a term that means whatever you like.

— Security and anti-fraud analytics will be a thing in 2016.  (They were also a thing in 2015.)

— Industry analysts are divided about whether or not the analytics talent crunch will persist.

— IoT is a great concept for selling data management tools, but few know how to make sense of it.

On ZDNet, Andrew Brust summarizes 60 predictions from 17 executives and sees the following:

  1. Increased adoption of streaming analytics
  2. Maturation of IoT technologies
  3. Value and maturity in Big Data products
  4. Increased deployment of artificial intelligence and machine learning

On KDnuggets, Gregory Piatetsky reports on five predictions for 2016 from Tom Davenport of the International Institute of Analytics.  (Webinar replay here.)

  1. Cognitive technology will be the next thing after automated analytics.
  2. Analytical microservices will facilitate embedded analytics.
  3. Data Science and predictive analytics will merge.
  4. The analytics talent crunch will ease due to increased enrollment in graduate programs.
  5. Analytics will focus on data curation and management.

Davenport is smoking something if he thinks cognitive computing will be a thing in 2016.

In Forbes, Gil Press synthesizes the IIA’s predictions (above) with predictions from Forrester, IDC and Gartner to get six predictions:

  1. Analytics will be embedded everywhere.
  2. Machine learning will replace manual data wrangling.
  3. The shortage of analytics talent will persist.
  4. Analytics projects will be riskier than typical IT projects.
  5. Cognitive computing will be the next buzzword.  (Press clearly does not agree with Davenport).
  6. Data monetization will take off.

Predictions (2) and (3) conflict with one another; since analysts spend 80% of their time data wrangling, tooling that automates this step will relieve the talent shortage.

On Datanami, Alex Woodie wades through “dozens” of predictions and publishes the 33 most interesting.  Many of these are self-serving, obvious or nonsensical, so I will do the work Woodie’s editor did not do and distill the list to five:

  1. Streaming analytics will mature and prove its worth.
  2. Apache Kafka will be an essential integration point in enterprise infrastructure.
  3. Business user access to Hadoop data will improve.
  4. Spark will significantly displace MapReduce for Hadoop workloads.
  5. Spark processing outside of Hadoop will also increase significantly.

Teryn O’Brien of Silicon Angle reports on a webinar hosted by Alteryx that included Bob Laurent of Alteryx, Clarke Patterson of Cloudera and Francois Ajenstat of Tableau.  The panel offered three predictions:

  1. Analyst jobs will be hot and analysts will be everyday heroes.
  2. Spark, the cloud and IoT will be big in 2016.
  3. Advanced analytics will play a key role in the Presidential election.

On ITPortal, Dell’s Todd O’Brien predicts three things for 2016:

  1. The role of Citizen Data Scientists will expand and evolve.  (Me: WTF?)
  2. Analytics will significantly affect vertical markets, especially manufacturing.
  3. All innovation will trace back to analytics

On the first point, I think that O’Brien is trying to say that companies should buy analytics software that is easy to use, like what Dell offers.

On the FICO blog, FICO’s chief analytics officer Scott Zoldi offers five predictions for 2016:

  1. Streaming analytics will come of age in 2016.
  2. “Prescriptive analytics” (his term for anomaly detection) will be a must-have security technology.
  3. “Lifestyle analytics” (predictions embedded in consumer interactions) will integrate prescriptive analytics into daily life.
  4. Businesses will rethink Big Data governance.
  5. Fake data scientists will emerge.

On a SAS blog, Polly Mitchell-Guthrie predicts five things:

  1. Machine learning (will be) established in the enterprise.
  2. IOT hype hits reality.
  3. Big Data moves beyond hype.
  4. Analytics improve cybersecurity.
  5. Analytics drives increased industry-academic interaction.

It’s standard practice at SAS to call any new IT trend “hype.”

In a press release, the health analytics vendor SCIO Health Analytics makes four predictions for 2016:

  1. Greater focus on educating health consumers.
  2. Demand for more precision in health analytics.
  3. More time will be spent on reimbursement strategies.
  4. The need for data and transparency across domains will increase.

Prediction #1 may be true, but it’s not really about health analytics.

On the Talend blog, CMO Ashley Stirrup predicts four things:

  1. Real-time analytics will take center stage
  2. New business threats will emerge
  3. CIO turnover will accelerate
  4. Businesses will retool

#2 and #4 aren’t really predictions, they simply state the obvious.

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