Break out the popcorn and the lemonade folks, it’s that time of year again! A few days ago, Gartner released its 2014 Magic Quadrants — an analysis of business intelligence and analytics software – and this year is a doozy.
The business intelligence and analytics software marketplace has, in my opinion, been a bit of a mess for the last few years. Reporting, data visualization and statistical inference have been hot on enterprise IT roadmaps – and there’s been no shortage of vendors out there offering software packages to handle those functions — but the variety of names we’ve used for those functions, and the widespread price points for the software has been a source of confusion for buyers.
The good news is this year, I think Gartner has the list of features right, and broken the marketplace down in ways that will help buyers decide what they really need.
Who’s Gartner?
Gartner, Inc., is a U.S.-based information technology research firm. If I want to know which product to buy for my clients or how to solve an enterprise IT strategy problem, my first step is usually to track down a Gartner paper, or one of its competitors’ papers, for more information. Gartner’s work is great – and as such, it isn’t free. Corporate users can subscribe to Gartners’ services, or buy its papers individually for a few hundred dollars each.
What are the Magic Quadrants?
Of particular interest to CIOs and IT directors are Gartner’s Magic Quadrants papers, which for a given type of software, evaluate the offerings from the major vendors in that industry and provide their thoughts on what each package does well, what it doesn’t do, and how it compares to the competition.
Magic Quadrant papers aren’t free – but are often distributed far and wide by vendors that rank well in a given report. You can read the two papers I’m discussing today here:
- SAS shared the Magic Quadrant for Advanced Analytics Platforms paper and posted a sponsored link in a Feb. 24 press release.
- Tableau Software did well in the Magic Quadrant for Business Intelligence and Analytics Platforms paper and posted a sponsored link a recent press release.
What Did the Papers Say and Why Should I Care?
Gartner comes out and says it: Tableau does data visualization right, Microsoft and IBM do enterprise data – no one does both well.
I’ll probably write a whole post on this at some point – but for now, let me say the tools your department managers like to use for data analysis don’t really work for enterprise-wide reporting and vice versa. Tools such as Tableau and QlikView are leading the pack this year driven by users’ love of their easy data-exploration capabilities. The trouble is, IT generally dislikes those tools because they’re too expensive for users who just want to view and refresh pre-built reports – and because they don’t fit well into big IT enterprise data governance plans.
On the other hand, tools from Microsoft, IBM, and SAP allow for well-planned, secure roll-outs of inquiry tools and data sets that mean what the company wants them to mean – but the report-writing tools that ship with those packages aren’t quite as fun to use.
“Business Intelligence and Analytics Platforms” vs.
“Advanced Analytics Platforms”
Part of the confusion for me in the last few years of Magic Quadrants reports was in explaining to folks that even though the industry used the word “analytics” to describe the business intelligence and reporting software from vendors such as SAP BusinessObjects, Tableau and Microsoft – and to describe the statistics packages created by companies such as SAS, RapidI and Stata, those tools were used for very different purposes.
This year, though, Gartner released two different Magic Quadrants: “Magic Quadrant for Business Intelligence and Analytics Platforms” and “Magic Quadrant for Advanced Analytics Platforms.” I think this is a great move that allows for a more apples-to-apples comparison of tools and easy identification for market leaders.
They list out the functions these tools should have – and give them names. One of the reasons I love Gartner reports is they list out the feature categories their reviewed toolsets share, and provide a set of names for those functions that a lot of us in a given industry will agree on.
Here are a few that will help you get the idea – and distinguish between the two big categories.
Business Intelligence and Analytics Functions
Business intelligence and analytics toolsets help organizations build, manage and distribute analysis to a broad set of users. For 98 percent of you out there, this is what you’re talking about when you refer to “analytics” software. It’s a huge category, and covers solutions of all kinds, big and small, cheap and terribly expensive.
Names you hear most frequently will include IBM Cognos, SAP Business Objects, Microsoft Excel, Microsoft Power BI, Tableau, and MicroStrategy. Functions include:
- Information delivery:
- Dashboards
- Ad hoc reporting
- Mobile BI
- Analysis:
- Interactive visualization
- Geospatial analysis
- OLAP
- Integration:
- BI infrastructure and administration
- Metadata management
- Collaboration, big data source support
Advanced Analytics Functions
Advanced analytics software packages tend to be smaller in scope and less widely used than business intelligence packages. They also vary widely in feature sets.
In general, this category includes statistics packages such as IBM’s SPSS and SAS’s various offerings. And although there’s been a move of late for vendors to roll advanced analytics functions into their larger business intelligence suites, we’re not there yet. Unless you’re an academic or a trained data analyst, you probably don’t need this stuff. Functions include:
- Advanced descriptive analytics:
- Clustering and self-organizing maps
- Affinity and graph analysis
- Similarity metrics
- Predictive analytics:
- Regression modeling
- Time-series analysis
- Neural nets
- Classification and regression trees
- Optimization and simulation:
- Solver approaches
- Design of experiments
- Monte Carlo simulation
- Further advanced analytics:
- Text and multimedia analytics
- Geospatial analysis
- Financial modeling and other pre-configured business models
Download our guide to learn more about how data analytics can help your business:
DataClear is a Baton Rouge-based data analytics consulting firm. Contact us for a free 30-minute consultation and discover how your company can profit from data-driven decision making using tools that won’t break your budget.