Analytics, Business Intelligence Are Converging, not Merging
Enterprise Apps Today recently wrote about Gartner's new Magic Quadrant (MQ) specific to advanced analytics. Gartner addresses the broader business intelligence market in its Magic Quadrant for Business Intelligence and Analytics Platforms, which also encompasses analytics capabilities – so, yes it can get a little confusing.
To better reflect the evolution of the market, the analyst firm seeks to differentiate the more advanced analytics functions from mainline BI. Rita Sallam, primary author of the MQ for Business Intelligence and Analytics Platforms, explained that the market is in the midst of transformation. While there are BI systems used for measurement and reporting, a growing number also support analysis, prediction, forecasting and optimization.
Traditional business intelligence is not going away, Sallam said. In fact, she believes it will remain an essential element of the enterprise application toolset.
“Traditional BI functions will always play a role in enterprises even as they expand their analytics initiatives by adopting advanced types of analytics. The need to report on key predictive indicators and actual results of predictive models will still have to measured,” she said.
Because most companies lack the skill sets to deploy advanced analytics pervasively, one trend emerging is tools that automate running the right algorithms behind the scenes to automatically serve up visualizations and identify key patterns in data to users.
“Embedding advanced analytics in applications, business process or dashboards (within traditional BI) targeted at BI consumers or non-traditional BI users will be another way to expand pervasiveness,” said Sallam.
Business Intelligence Leaders
While startups and open source players filled many of the top spots in the advanced analytics MQ (with only SAS and IBM in the “Leaders” quad), in this report the mega-vendors and more established players did much better. Microsoft, SAP, SAS, IBM and Oracle all landed in the “Leaders” category, along with business intelligence stalwarts such as Information Builders, MicroStrategy, Tableau, Tibco and Qlik.
Others knocking on the door of the “Leaders” quadrant include Birst, Panorama, Alteryx and Pentaho. Like the advanced analytics quadrant, this list shows a strong representation among open-source vendors. Pentaho, for example, is built on an “open core” model with a commercial version with advanced visualizations and enterprise scale capabilities on its way, as well as customer support and additional services.
“Open source is the key to driving our rapid innovation, including in the Big Data market,” said Quentin Gallivan, chairman and CEO of Pentaho.
Pentaho Business Analytics 5 couples analytics with data integration and data blending. It is embeddable in software-as-a-service (SaaS) applications, cloud and business processes. Gartner praised these capabilities and highlighted its low cost of licensing. But the report raised concerns about slightly below average product quality and support, as well as some difficulty to use and implement it.
Gallivan said that many of these issues were taken up in the platform redesign for Pentaho 5.0. He also called attention to a note in the MQ where Gartner pointed out that many of its cautions were due to only 20 percent of the survey respondents being on the current version of the platform. Further, he noted that Pentaho made the greatest movement on the MQ of any vendor in improving its performance compared to last year.
“Big Data technologies are advancing at speeds like never before, and the upper right quadrant of the MQ is open territory,” said Gallivan. “Vendors need to be nimble with the mindset of relentless innovation balanced with product support.”
While Pentaho is striving to enter the top bracket for business intelligence platforms, SAS has been a Leader in this MQ for the last nine years, said Malene Haxholdt, Global Analytics marketing manager at SAS.
According to Gartner, one of the the strengths of SAS is a portfolio that spans BI, performance management, data warehousing, in-memory databases, data integration, data quality, and content and social analytics. This is backed up by an underlying core competency around advanced analytics. Data mining, predictive modeling, simulation and optimization have long been part of the SAS mindset. This pedigree earned it Leader spots in both the Magic Quadrant for Advanced Analytics Platforms and the BI MQ.
Sallam noted that SAS tools continue to be the primary domain of power users, data scientists and IT-centric BI developers. While the company is working hard to add ease-of-use features, Gartner found SAS scored poorly on some indexes due to the product's complexity. This is being addressed via SAS Visual Analytics, a more business-oriented data discovery and BI platform that can be used by less technical users. By giving this strategic importance, Gartner believes SAS has made the right move to defend its position against encroachment by BI startups and the open source community.
Gartner also worries that SAS could miss out on business, as it may not end up on an organization's BI platform evaluation shortlists unless the organization already uses SAS for its advanced analytic capabilities. Additionally, Gartner surveys showed lower-than-average ratings on reporting, dashboards, online analytical processing and interactive visualization functionality.
SAS believes this is being addressed via its Visual Analytics emphasis and by the fact that the market is seeing an inexorable convergence occurring in this area.
Analytics on the Upswing
“What we’re seeing is a market convergence of traditional BI and advanced analytics,” said Haxholdt. “There is still a need to report on information, but what’s happening is a recognition that information needs to be more accurate, so analytics are a bigger part of the convergence trend.”
The results of descriptive business intelligence and predictive analytics need to be more consumable by more people, she said. “As part of that trend, reporting technologies are being modernized to make it easier to understand data through techniques like data visualization and new means of reporting like viewing reports on mobile devices.”
Gartner analyst Gareth Herschel, an author of the MQ for Advanced Analytics Platforms, isn’t so sure that convergence is inevitable, however. “I think we will see increasing areas of overlap, but I wouldn’t say I see them consolidating,” he said.
What is certain is that in whatever guise, the BI/analytics/advanced analytics space is one of the most prosperous areas within the enterprise application sector. Gartner puts the BI platform market alone at $14.1 billion for 2013. With the advanced analytics and Big Data sides growing exponentially and being steadily incorporated into these BI platforms, look for this zone to expand even further in the coming years.
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in California, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.
