Virtualization Technology News and Information
ScaleOut Software 2016 Predictions: Operational Intelligence Lifts Off

Virtualization and Cloud executives share their predictions for 2016.  Read them in this 8th Annual 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.

Published Thursday, December 31, 2015 6:34 AM by David Marshall
There are no comments for this post.
To post a comment, you must be a registered user. Registration is free and easy! Sign up now!
<December 2015>