Business intelligence (BI) is an evergreen that simply refuses to give up and get commoditized. Even though very few vendors try to differentiate these days on commodity features like point and click, drag and drop, report grouping, ranking, and sorting filtering (for those that still do: Get with the program!), there are still plenty of innovative and differentiated features to master. We categorize these capabilities under the aegis of Forrester agile BI; they include:
- Making BI more automated: suggestive BI, automatic information discovery, contextual BI, integrated and full BI life cycle, BI on BI.
- Making BI more pervasive: embedding BI within applications and processes, within the information workplace, and collaborative, self-service, mobile, and cloud-based BI.
- Making BI more unified: unifying structured data and unstructured content, batch and streaming BI, historical and predictive, and handling complex nonrelational data structures.
- Breaking through BI limitations: exploration and discovery, flexible and adaptable data models, and advanced data visualization.
It’s with BI unification (historical and predictive) in mind that SAP announced its intent to acquire KXEN. It’s not a major direction change for SAP, which has had a long history of providing predictive analytics functionality integrated with the rest of the BOBJ and BW technologies. For years, SAP OEMed SPSS as its predictive solution of choice. Once IBM acquired SPSS, that relationship naturally withered and SAP started building its own proprietary predictive routines in BW and HANA. SAP also got on the open source R bandwagon and integrated R into BOBJ and HANA. Now it’ll be interesting to watch how SAP will juggle its own proprietary predictive routines with R and KXEN. Also, please take a look at my friend and colleague Srividya Sridharan’s take on this acquisition specifically from a marketing and customer intelligence point of view.
SAP has tons of competition in this space:
- Just about every single leading BI vendor (including Actuate, Information Builders, MicroStrategy, Tibco Spotfire, QlikView, and Tableau Software) provides some level of integration with R.
- SAS has been in the predictive analytics and BI market for decades.
- IBM Cognos has tight integration with SPSS.
- Oracle OBIEE can call Oracle data-mining routines embedded into its DBMS.
- Microsoft Excel and SQLServer come with a dozen or so basic predictive routines built in.
We are currently evaluating all of these leading BI vendors against a few hundred criteria, including the following criteria on the intersection between BI and predictive analytics:
- The number of predictive routines that come out of the box with the BI platform
- Whether the vendor has its own proprietary software or OEMs it from a third party
- How tightly the predictive routines are integrated with the rest of the BI platform
- Whether the vendor’s BI platform integrates with or embeds R
- Whether the vendor provides a point-and-click GUI to generate R code
- Whether predictive routines can be imported and exported via PMML
Stay tuned for the results in December 2013.