There is no shortage of advice if you’re in the market for a “BI on Big Data” solution or as we sometimes like to call it “Big BI”. Big BI refers to a Business Intelligence (BI) platform that conforms with end-users needs (typically seamlessly integrated with Tableau or Excel), that can scale on any data size to deliver top query performance.
A resource you might find particularly interesting when sizing up your BI tools, is the latest version of the “G2 Crowd Grid for Business Intelligence Software”. The Winter 2016 version just got published. We reviewed the grid and its report and found some interesting insights worth sharing.
Get the G-2 on G2
First, a little bit about the G2 Crowd Grid:
- G2 is not Gartner: Despite the assumptions you could draw as it relates to the company’s name, G2 Crowd is not associated with Gartner. G2 Crowd is a B2B software review site, whose content is mainly fueled by the unfiltered reviews of end-users.
- G2 Crowd is about the crowd's opinion: it has more than 100,000 verified user-reviews of business software.
- G2 is wide, not as deep: G2 Crowd receives more than 700,000 visitors per month and the average visit lasts more than five minutes. Site visitors are researching or reviewing business software from more than 400 different categories.
Because of these reasons, you might think that G2 analysis is wide but not necessarily deep. We advise that you complement their analysis with research from Gartner. In fact, if you want to catch-up on the latest trends highlighted in the Gartner Magic Quadrant for Business Intelligence (BI) 2016, take a look at this write-up.
Who's got the Biggest BI?!
Interestingly enough, the G2 Grid looks very similar to the Gartner Magic Quadrant. It has 4 key categories (Leaders, Contenders, Niche and High Performers). And, it would seem that the further to the top right a vendor is, the better the quality and performance.
The value on the G2 Grid axis are different from Gartner though. Gartner assesses companies against Execution and Vision. G2 looks at Market Presence and Satisfaction.
- Gartner had 24 vendors in its Quadrant. G2 has 26.
- G2 is more lenient. It has 5 companies in the leader box. Gartner has 3.
- G2 is more hopeful. It has 9 vendors in its contender box. Gartner has 0.
Finally, Gartner places a lot more vendors in a niche category (11) whereas G2 only sees 4. This might simply be due to the fact that end-users reviewing their own solutions think about their use-case as “the market” whereas Gartner tends to look at broader solution-set and larger customer base before they decide to move them out of the niche box.
We’ll let you review the rest of the research for yourself and for your own use case, but, at first view, some of the below observations might be interesting to you:
- The average age of the BI companies evaluated is 22 years. Or, to be fair to the extremes, consider this: the median age of your BI provider is 16 years.
- BI 1.0 vendors like SAP BusinessObjects, IBM Cognos, Hyperion and MicroStrategy are all lumped in the contender box, all the way to the left (the “low satisfaction corner”).
- Yet, when the Grid data is filtered for the Enterprise Segment only (see below), most move to the right. Oracle BI and Hyperion in fact become leaders. MicroStrategy gets the lowest “Likely to Recommend” score and a negative Net Promoter Score (NPS).
- It takes more than 2 months to go live with a BI tool on average. To be more exact, it’s closer to 73 days, although 4 of the BI tools evaluated don’t have any stats.
- Average User Adoption is 50%. That’s better than the 25% adoption rate we used to read about in the early days. It’s still pretty bad though. Think about it. Half of the people you’re deploying these tools for are not using it!
- Big Data Services and Modeling capabilities get low satisfaction scores. While functionality satisfaction hover over the 85% satisfaction score, “Big Data Services” gets 83% and “Modeling” gets a 73% satisfaction score.
After reviewing Gartner and G2’s views of the market, I’m not sure, who’s got the biggest eye on BI this year!
However, if you are looking to scale BI for Big Data, I know there are three key resources you should probably check out. Here they are below:
For everything else, contact us here!