In November I wrote two parts of a planned multi-post series on issues in analytic technology. Then I got caught up in year-end things and didn’t blog for a month. Well … Happy New Year! I’m back. Let’s survey a few BI-related topics.
Mobile business intelligence — real business value or just a snazzy demo?
I discussed some mobile BI use cases in July 2010, but I’m still not convinced the whole area is a legitimate big deal. BI has a long history of snazzy, senior-exec-pleasing demos that have little to do with substantive business value. For now, I think mobile BI is another of those; few people will gain deep analytic insights staring into their iPhones. I don’t see anything coming that’s going to change the situation soon.
BI-centric collaboration — real business value or just a snazzy demo?
I’m more optimistic about collaborative business intelligence. QlikView’s direct sharing of dashboards will, I think, be a feature competitors must and will imitate. Social media BI collaboration is still in the “mainly a demo” phase, but I think it meets a broader and deeper need than does mobile BI. Over the next few years, I expect numerous enterprises to establish strong cultures of analytic chatter (and then give frequent talks about same at industry conferences).
Business intelligence for mid-market enterprises is problematic
Given the saturation of the large-enterprise BI market with supposed enterprise-standard BI systems, it would seem that smaller enterprises comprise a large part of the BI growth opportunity. However, the large-enterprise and mid-range BI markets are very different. For example:
- Large enterprises typically have tough challenges in data integration; smaller enterprises may truly start out with their data in only a few systems.
- There are many reasons for large enterprises not to do their BI in the cloud, such as bandwidth, internal politics, or the unsuitability of most cloud infrastructure for analytic DBMS scale-out. Smaller enterprises, however, may prefer SaaS (Software as a Service) BI.
- The BI market for smaller enterprises is heavily OEM. But unless you’re buying some kind of data/analytics bundle, the large enterprise BI market still seems overwhelmingly standalone.
- Large-enterprise BI tools incorporate much of a DBMS-like technology stack; at smaller enterprises, BI can often stick to its specialized-application-development-tool knitting. But on the other hand …
- … large enterprises almost always already have a data warehousing infrastructure. Mid-range BI buyers may not have a separate analytic DBMS. Therefore …
- … BI/DBMS bundles make more sense in the mid-market than they do at large enterprises.
- Each large enterprise has a unique infrastructure, and commonly a unique competitive situation as well. Thus, the idea that you’ll pre-build most of an analytic application for a large enterprises — because you know what data model they need to do their BI — usually turns out to be silly. But smaller enterprises can be more homogeneous, and so for them pre-built analytic applications can actually work.
I don’t know of anybody who’s really cracked the code on mid-market BI. Crystal Reports (long owned by SAP Business Objects) has huge OEM share, but somehow hasn’t parlayed that into a comprehensive mid-market BI presence. Various SaaS or on-premise vendors have cool product ideas — e.g. Gooddata, Endeca, or my clients at PivotLink — but none seems to have set the world on fire to this point.
Departmental BI is doing better
The news is happier in a related market — business intelligence for departments of larger enterprises. However, this is a hard market to analyze, for at least two reasons. First — as is often the case — the distinction among large-enterprise-wise, smaller-enterprise-wide, and departmental BI is not a clear one.* Second, “departmental BI” has at least two major strains:
- Simple, pedestrian BI, implemented quickly.
- Investigative analytics.
*In particular, it has been the case since the 1990s that BI tools first get sold to departments, hopefully for fast implementations — think 4-6 weeks as a base case — and then spread out internally after their initial successes. I am frequently amused by vendors who claim to have pioneered that sales model sometime over the past decade, or even within the past few years.
That said, there are two main kinds of reason to do your BI departmentally, at arm’s length from central IT.
- Perhaps, for good reason or bad, IT is being insufficiently helpful at managing the data.
- This can be a straightforward matter of politics and priorities — IT controls the data, but is slow about giving you access.
- Also, you may want to include data that’s outside IT’s purview, be it third-party or just purely departmental.
- Further, you may want functionality that corporate-standard BI doesn’t offer.Potential examples include:
- Cool analytic visualization.
- “Real-time” data visualization.
- The ability to play nicely with particular kinds of data sets.
I have a lot more to say about those points — but not in a post that’s already as long as this one.