
Virtualization and Cloud executives share their predictions for 2016. Read them in this 8th Annual VMblog.com series exclusive.
Contributed by Dr. William Bain, CEO of ScaleOut Software
Operational Intelligence Lifts Off
Operational Intelligence gained traction in 2015, as more enterprises
began realizing the benefits of analyzing live, fast-changing data to gain immediate
business insights. In 2016, organizations will take the next step as they find
new ways to use in-memory computing as an enabling technology for operational
intelligence. In addition to anticipating increasing demand for operational
intelligence, ScaleOut Software expects Microsoft to maintain focus on its
"cloud-first, mobile-first" initiative, and it expects that Spark's dominance
as a catch-all big data solution will be challenged by other analytics
technologies optimized for specific business use cases.
Companies will shift toward a hybrid approach
to data analytics that marries traditional, offline analysis with operational
intelligence.
To keep pace with the dynamic
needs of customers, ScaleOut anticipates that enterprises will shift toward a hybrid approach to big data analytics that
marries the use of traditional analytics tools for static data sets with
in-memory computing technologies for analyzing fast-changing data within live
systems. As in-memory computing increasingly enables operational intelligence,
enterprises will gain the ability to track fast-changing data, build evolving
models of users and systems, and thereby steer their behavior with extremely
low latency. This will open the door to capturing important new business
opportunities that otherwise would be lost.
In
2016, in-memory computing will become an important enabling technology that
increases the value of traditional business intelligence by
extending it to live user or machine activities and capturing perishable insights that
otherwise would be missed.
One
research group, Markets and Markets, believes the in-memory computing market is
expected to grow to $23.15 billion by
2020. Likewise, Gartner supports the premise that in-memory
computing will be a disruptive
force in IT over the coming year. While there will always be a place for traditional
data analysis tools, the ability to complement them with operational
intelligence will become a key asset offered by in-memory computing.
To implement its recent strategy of pushing
enterprises towards their "cloud-first, mobile-first" world, Microsoft will
continue to aggressively migrate users away from legacy technologies, and third-party
vendors will rise to the occasion with innovative solutions.
As seen with Windows 10 and Systems
Center Configuration Manager, Microsoft is rapidly migrating users away from legacy
software and toward alternatives that help establish its industry leadership
with the Azure cloud platform and mobile technologies. In many cases, this will
open the door for enterprises to switch to other solutions that offer them deep
technology with quick, easy migration. For example, as Microsoft looks to pull
the plug on Windows Server AppFabric support in 2017, IT
professionals are seeking alternative technologies from third-party vendors
that provide a seamless transition and a more comprehensive feature set.
Similar to
Hadoop, Apache Storm and others before it, in 2016 Spark's popularity will begin
to peak as real-world enterprise applications probe the limits of its
capabilities and alternative technologies compete for attention.
Similar to Apache Hadoop before
it, in 2016 Spark will continue to climb the hype cycle
of open source, which relentlessly fuels fast-growing developer communities.
However, Spark will not turn out to be the silver bullet that addresses all big
data challenges. While it will continue to dominate as an effective alternative
to both MapReduce and other streaming technologies, its limitations for operational
intelligence within live systems will become increasingly clear.
Enterprises will begin evaluating
alternative in-memory computing technologies that allow them to go beyond
Spark's approach to data-parallel computation and tackle in-the-moment analysis
of live systems, model their evolving behavior, and provide important feedback
that steers behavior. This will deliver a wealth of new insights and previously
untapped value to business stakeholders.
This year, enterprises barely scratched
the surface of operational intelligence. In 2016, as more companies incorporate
in-memory computing technology within their live systems, the exciting
potential for operational intelligence will become reality, and adoption then should
rapidly accelerate.
About the
Author
ScaleOut
Software was founded in 2003 by Dr. William L. Bain. Bill has a Ph.D. (1978) in
electrical engineering/parallel computing from Rice University, and he has
worked at Bell Labs research, Intel, and Microsoft. Bill founded and ran three
start-up companies prior to joining Microsoft. In the most recent company
(Valence Research), he co-developed a distributed web load-balancing software
solution that was acquired by Microsoft and is now called Network Load
Balancing within the Windows Server operating system. Dr. Bain holds several
patents in computer architecture and distributed computing. As a member of the
screening committee for the Seattle-based Alliance of Angels, Dr. Bain is
actively involved in entrepreneurship and the angel community.