Advanced Analytics: Believe the Hype
By 2018, Gartner projects that advanced analytics will underpin the competitive efforts of more than half of all large organizations.
- By Steve Swoyer
- February 26, 2016
Which is the fastest growing segment of the business intelligence (BI) market of them all?
According to market watcher Gartner Inc., it's advanced analytics, which the firm says will eclipse $1.5 billion this year on the strength of a 14 percent growth rate. That isn't necessarily surprising.
What's surprising is that sales of advanced analytical technologies and services hasn't already eclipsed $1.5 billion. It's certainly among the most hyped of BI-related technologies, after all.
In this case, the hype seems warranted, Gartner suggests. "Advanced analytics has already been changing entire industries for over a decade and is a key factor for how most new entrants disrupt established markets and beat their incumbents -- whether selling books, renting movies, borrowing money[,] or even building a professional sports team," said Gartner research director Jim Hare in a prepared release.
Hare is a BI industry veteran of some standing. Most recently, he headed up product marketing with Actian Corp; prior to that, he was in charge of big data product marketing and strategy with IBM Corp. His recent history goes all the way back to Celequest Corp., a dashboard appliance specialist the former Cognos Inc. acquired back in 2007.
By 2018, Hare and Gartner project, advanced analytics -- and optimized, in-house algorithms -- will underpin the competitive efforts of more than half of all large organizations.
"Today, with fewer regulated monopolies and the Internet eliminating geographical boundaries, more companies are starting to use statistical analysis, predictive modeling and decision optimization to compete, instead of using traditional approaches," Hare noted.
The upshot, Hare says, is that organizations that expect to successfully manage this transition can't expect to gradually shift their spending from backward-looking BI and light-analytic investments. Instead, he argues, they must invest aggressively in advanced analytic technologies. The transition will be complicated by virtue of the complexity of the field -- advanced analytics encompasses machine learning (ML), data mining, and statistical analysis, but also the use of advanced numerical methods -- and the comparative scarcity of math- and business-savvy human resources.
As Hare notes, a number of "leading" organizations are already developing proprietary algorithms to take the guesswork out of business decision making. So-called "proprietary" algorithms aren't necessarily new or original. What's meant, instead, is the use of existing -- and, in some cases, newly developed -- algorithms in predictive models designed and optimized for an organization's business.
Also by 2018, Gartner forecasts the appearance of algorithm marketplaces, which it believes will be combined with platform-as-a-service (PaaS) to help simplify the adoption of advanced analytics, promote easier (and more secure) data sharing, and support an emergent market in saleable raw data. Raw data is essential grist to the advanced analytic mill, according to Gartner: with more (and more varied) detail data, machine learning and other kinds of predictive models models can be optimized and trained more quickly -- and can produce much better results.
By 2018, the market watcher says, new technologies, practices, and processes will emerge to address most of the issues (e.g., trust, data prep, and licensing) that today inhibit the sharing or sale of data. "Today's situation of sharing data is problematic," said Alexander Linden, research director at Gartner, in a release. "Data providers don't typically trust end users with detailed, event-level data. On the other hand, data consumers do not like the involved complexities of data licensing and data integration. As a result, there is a significant impediment to sharing and monetizing data."
About the Author
Stephen Swoyer is a technology writer with 20 years of experience. His writing has focused on business intelligence, data warehousing, and analytics for almost 15 years. Swoyer has an abiding interest in tech, but he’s particularly intrigued by the thorny people and process problems technology vendors never, ever want to talk about. You can contact him at [email protected].