By Alex Woodie
What will happen in big data in 2016? You’d think that would be a cinch
to answer, what with all the deep neural net and prescriptive analytic progress
being made these days. But in fact the big data predictions from the industry
are all over the map.Datanami received dozens of predictions from
prominent players in the industry. Here is a culled collection of the most
interesting ones.
Oracle sees the rise of a new type of
user: the Data Civilian. “While complex statistics may still
be limited to data scientists, data-driven decision-making shouldn’t be,” Big
Red says. “In the coming year, simpler big data discovery tools will let
business analysts shop for datasets in enterprise Hadoop clusters, reshape them
into new mashup combinations, and even analyze them with exploratory machine
learning techniques.”
Nucleus Research is
going out on a limb and predicting the death of big data as we
know it. “In the past two years everyone and their dog seems to have launched a
big data solution of some kind. It’s time for the shiny object syndrome to
stop,” it says. “Instead of attacking the monolithic and daunting task of big
data analysis, users will approach and access it like any data.”
Since even canines are pulling down big VC money for data startups, it
may be time to start asking tough questions, according to Keri
Smith, senior vice president at Opera Solutions.
“What is the real ROI of a big data solution?” Smith asks. “How can companies
get beyond departmental deployments to maximize the value of big data across
the enterprise? And what are the meaningful use cases across a variety of
verticals? If your company isn’t asking these questions and actively seeking
answers, it should soon.”
We’ll see the rise of Data Jedis in 2016, says Matt
Bencke, CEO of Spare5. “More jobs will be
changed by AI than ever before and the ‘Data Jedis’ will become the most sought
after employees,” he writes. “Machine learning+human insights will infiltrate
new industries including healthcare and security and employees will need to adapt
to providing a different service or get left behind in 2015.”
Data science will be big in banking, predicts Mike Weston,
CEO of data science consultancy Profusion.
“The financial industry is one of the pioneers of data science techniques,” he
writes. “Nevertheless, the adoption of data science has been far from uniform
across all banking services. In 2016 I expect this picture to change. Better
use of data and personalisation of services will move from the financial
markets to retail banking. It will have a profound impact on marketing,
customer service and product development.”
The prospect of advanced AI giving rise to robot overlords scares
Elon Musk. But according to Jans Aasman, a cognitive scientist and CEO ofFranz, AI should be placed the “friendlies”
column. “Artificial intelligence and cognitive computing will make personalized
medicine a reality, help save the lives of people with rare diseases and
improve the overall state of healthcare in 2016 and beyond,” he says.
Chief Data Officers (CDOs) will become the “new it girl” of
information tech, complicating office politics forever, argues Michael Ludwig,
head of Blazent’s Office of the
CTO. “Driven by the complexity of big data and the need for complete and
accurate data, the CDO will become increasingly important,” he writes. “As a
result, the CTO and CIO will need to make room for the CDO, and tension will
emerge within the C-suite until clearly defined roles and associated teams are
established.”
Not everybody sees it that way, including Craig Zawada, Chief Visionary
Officer at PROS. “In 2016, we’ll
begin to see erosion in the appointment of Chief Data Officers, a role of the
past. Instead, Chief Insight Officers will emerge in 2016 as
crucial leaders in the big data compilation process.”
CIOs, yeah baby!
But can the mighty CIO get his mojo back? Cazena founder and CEO Prat Moghe’s looks
into his crystal ball, and says it’s so. “In 2016, CIOs will take advantage of
enterprise-ready cloud services to become brokers of cloud services that meet
IT mandates for governance, compliance and security as well as business needs
for agility and responsiveness,” he writes.
Streaming analytics will start to mature and prove its worth in the big data lineup,
predicts Phu Hoang, the CEO and co-founder ofDataTorrent. “While lots of companies have
already accepted that real-time streaming is valuable, we’ll see users looking
to take it one step further to quantify their streaming use cases. In the next
year, customers using streaming tools will reach new levels of sophistication
and demand a quantified ROI for streaming analytics,” he says.
Real-time analytics will be hot next year. We get it. But one
technology—Apache Kafka–stands taller than the rest, according to MongoDB‘s VP of strategy Kelly Stirman. “Kafka
will become an essential integration point in enterprise data infrastructure,
facilitating the creation of intelligent, distributed systems,” Stirman writes.
“Kafka and other streaming systems like Spark and Storm will complement
databases as critical pieces of the enterprise stack for managing data across
applications and data centers.”
Like drums? Then you’re going to love 2016, says Badri
Raghavan, the chief data scientist at FirstFuel
Software. “In the months ahead, we will see organizations and
individuals tap data and analytics to deliver personalized and engaging
experiences across industries including energy, sports, social good and music.
For instance, people will be able to use data to change a song based on their
personal preferences (e.g., lots of drum).”
How will the IoT impact the semiconductor business? IT legend Ray
Zinn has a few thoughts on that. “You will see greater divisions
between design and fabrication,” he writes. “Fabs will have the mission of
scale to serve a few billions consumers and the nascent Internet of Things
(IoT) markets. Design will become uniquely divorced from fabrication, splitting
the market risk. Design firms will survive best by innovation, and fabs through
ruthless efficiency. The question is what comes next? There will inevitably be
new markets and devices that will drive a new growth spurt. The IoT is the
sleeping giant, but I doubt the only one snoozing.”
Machine learning, big data automation, and artificial
intelligence were big in 2015, and will get bigger next year, says
Abdul Razack, SVP & head of platforms, big data and analytics at Infosys.
“In 2016, the pace at which enterprises more widely adopt artificial
intelligence to replace manual, repetitive tasks will rapidly increase,” Razack
says, citing the $1 billion AI investmentmade recently by
Toyota. Big data automation is already growing, but next year “it
will be more widely used to accentuate the unique human ability to take complex
problems and deliver creative solutions to them.” The self-driving
cars from Tesla have built-in machine learning, but next year,
“machine learning will quietly find its way into the household, making the
objects around us not just connected.”
Lots of people see exciting things happening in the
big data space in 2016. Not Charles Caldwell, the vice president of solutions
engineering and services at Logi Analytics. “When
I look ahead to 2016, I don’t see a lot of exciting things happening. Other
vendors have come out with their predictions around cloud, visual analytics and
mobile, but most of those things are old trends that are settling down. In my
opinion, 2016 will be a year of consolidation and ground building for the next
big thing.”
The “Not In Your Wildest Dreams” award goes to Peter Eicher,
senior manager for product marketing at Catalogic Software. We’re not talking
about his prediction that copy data management (CDM) “is a technology whose
time has come as evidenced not only by the new vendors in the space but by old
school players chiming in with ‘me too’ arguments.” That makes total sense. No,
we’re calling Peter out for his crazy prediction that the New York Knicks win
the NBA Championship. “Yeah, not happening,” he admits. “I can’t be right all
the time. On the other hand, that prediction has been wrong for 42 years
running. One of these days….”
The “Debbie Downer” award for big data goes to BlueTalonCEO Eric Tilenius for his prediction
that the pace of big data breaches at major enterprises may rise. “In
2016, the lack of unified data governance could lead to the biggest security
disruption that enterprises have ever faced—comparable to the disruption caused
to the traditional enterprise perimeter by the entry of mobile,” he writes.
“Relying on a fragmented approach to control data access, where inconsistent
policies are applied across an ever-changing data landscape, will leave gaping
holes in the protection of enterprise data.”
Are you into microservices? If not, you will be soon,
according to SaaS heavy Workday.
“It’s clear that the on-premise versus cloud battle is over. Cloud has won,”
the company says. “Yet, not all cloud architectures will be created equal.
Microservices architectures will go beyond the realm of consumer Internet
designs like Netflix and become the most important architecture advancement in
enterprise applications since the shift to the cloud.”
Big data is hard, and companies will struggle with it
next year, says Ulrik Pederson, CTO of TARGIT.
“2016 will see an expansion of big data analytics with tools that make it
possible for business users to perform comprehensive self-service exploration
with big data when they need it, without major hand holding from IT,” he
writes. “Corresponding with my first predication, I anticipate a huge increase
in advanced analytics projects across industries. However, that doesn’t mean
they’ll be successful…. I wouldn’t be surprised to hear of many vendors and
customers struggling to implement successfully.”
The International
Institute of Analytics sees the rise of analytics microservices
to facilitate embedded analytics. The IIA also sees progress being made in
areas of cognitive technology, data science, and data curation. Oh, and the
analytics talent crutch will ease as many new university
program come online, the group says.
Elnur/Shutterstock.com
People who aren’t data geeks will get into the big
data swing of things, says Bruno Aziza, Chief Marketing Officer of
OLAP-on-Hadoop provider AtScale.
“As Hadoop becomes more accessible to non-data geeks, marketers will begin to
access more data for better decision making,” he writes. “Hadoop’s deeper and
wider view of data will enable marketers to capture behaviors leading to
decisions and understand the processes underlying customer journeys.”
We’ll see more HPC tech making its way into the
mainstream, particularly as it pertains to storage, predicts storage giant DDN. “Storage, data management and application
acceleration technologies from the HPC industry will continue being tapped at
even a higher rate in 2016 to meet the evolving requirements of performance and
scale and will replace traditional IT infrastructures at even a higher rate,”
the company says.
Spark will kill MapReduce, but save Hadoop, says Monte
Zweben, co-founder and CEO of RDBMS-on-Hadoop vendor Splice Machine. “MapReduce is quite
esoteric. Its slow, batch nature and high level of complexity can make it
unattractive for many enterprises,” he writes. “Spark, because of its speed, is
much more natural, mathematical, and convenient for programmers. Spark will
reinvigorate Hadoop, and in 2016, nine out of every 10 projects on Hadoop will
be Spark-related projects.”
But that doesn’t mean every Spark project will involve
Hadoop, says Bob Muglia, the CEO ofSnowflake
Computing. “Today, Spark is part of Hadoop distributions and is
widely associated with Hadoop. Expect to see that change in 2016 as Spark goes
its own way, establishing a separate, vibrant ecosystem. In fact, you can
expect to see the major cloud vendors release their own Spark PaaS offerings.
Will we see an Elastic Spark? Good chance.”
Organizations will reset on Apache Hadoop, says Dan Graham, general
manager of enterprise systems atTeradata.
“As Hadoop and related open source technologies move beyond knowledge gathering
and the hype abates, enterprises will hit the reset button on
(not abandon) their Hadoop deployments to address lessons learned –
particularly around governance, data integration, security, and reliability.
The junk drawer problem is one of the Hadoop
community’s biggest challenges. But never fear–Master Data Man(agement) is
here! “MDM will become ubiquitous,” writes Manish Sood, CEO and founder of Reltio. “MDM as a discipline has long only been
affordable by large companies with big IT teams and budget for hardware,
software and multi-year implementation projects…A new breed of data-driven
applications will come built-in with MDM as table stakes. As a consequence of
delivering both operational and analytical functionality, the reliable data
foundation of each application is powered by an MDM engine.”
Hadoop will be at a crossroads in 2016, but which fork
will it take? Mike Maciag, COO ofAltiscale,
give us his prediction. “In 2016, we will see industry standards for Hadoop solidify. In the beginning of 2015,
we saw the launch of the Open Data Platform Initiative (ODPi), which
established standards for how key projects in the Big Data ecosystem can work
together. ODPi doubled in membership during the course of the year as the
benefits to standardization for customers became even more clear. We expect to
see more growth and recognition in 2016, allowing new technologies and
applications to meet the Hadoop ecosystem standards being established by the
ODPi.”
We’ll see the emergence of IoT 2.0 predicts Zebra Technologies. “The IoT market will
transition to more mature, industry and adaptable solutions from what used to
be closed, proprietary first-generation offerings. With an open-source
approach, organizations will be able to choose from a larger pool of service
providers and their respective APIs.”
The IoT may hearken the rise of a post-scarcity economy,
predicts OpenText CEO Mark
Barrenechea. “Imagine algorithms as apps for applying big data analysis over
the connected masses of information generated by the IoT and its billions upon
billions of connected devices in every aspect of our lives,” he writes. “Owning
the data, analyzing the data, and improving and innovating become the keys to
corporate success—all empowered by a connected digital society.”
The rise of converged platforms that can handle both
analytic and transactional workloads will take a leap forward, foresees John
Schroeder, CEO of MapR Technologies. “In
2016, we will see converged approaches become mainstream as leading companies
reap the benefits of combining production workloads with analytics to adjust
quickly to changing customer preferences, competitive pressures, and business
conditions. This convergence speeds the ‘data to action’ cycle for
organizations and removes the time lag between analytics and business impact.”
Outsourcing will
be big in 2016, predicts Anil Kaul, CEO of big data service provider Absolutdata. “A gigantic amount of
valuable information can be generated from big data, but accessing this could
be challenging and it typically lies beyond the scope of routine business
intelligence,” he writes. “Many companies today are partnering with third parties
to create and execute big data analytics strategies. Integrating external
experts into the big data team may be the best way for companies to stay ahead
in this quickly evolving space.”
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