We cite collaboration as one of five key technology influences on the business intelligence (BI) market, and I get many questions about collaboration and BI from end users and vendors alike. The rise of social media websites such as Facebook and Twitter has raised awareness of collaborative platforms and created a critical mass of participants, which is a necessary ingredient for successful collaboration. However, I have to point out that consumer-oriented social media tools do not provide all the necessary components for collaborative BI.
There’s a big difference between analyzing social media data and collaborative BI. Social media provides a rich new source of data that many organizations found difficult or impossible to capture in the past. Analyzing various aspects of social media interactions can help an organization better understand its customers and how its products are faring in the market. Text analytics and sentiment analysis are useful techniques to analyze the actual content of the social media interactions. More traditional structured data analysis such as number of followers and number of mentions can be useful also. I refer to these aspects as social media analytics.
On the other hand, collaborative BI uses collaborative processes and technology to support and enhance an organization’s business intelligence activities. This concept has been around for some time. I worked on products 15 years ago that used workflow, annotations and email to create a collaborative environment. On a large scale, however, that never took off. These techniques persist today in software products, but they are not pervasive in the BI landscape. The rise in social media may change that, impacting BI in the same way that mobile technology has crept into BI infrastructure from the consumer side.
In fact, it already seems to be doing so. I was surprised when twice in one day I heard two large enterprises, Boeing and eBay, describe their uses of collaborative BI. Both occurred at the Teradata third-party influencers meeting. Boeing presenters told of consolidating a number of systems using Teradata and IBM Cognos 10. As they migrated from a number of disparate systems to a consolidated system, they used collaboration to gather input from users to validate that the new system was accurate and operating properly. The watchful eyes of the end users spotted issues that slipped through the formal testing process; this is a simple yet excellent example of using collaboration to enhance BI.
Oliver Ratzesberger of eBay shared a more complicated story that is the best enterprise instance of collaborative BI I have seen. Ratzesberger has spoken previously at Teradata events about eBay’s analytics as a service. The company employs a private cloud approach for its analytical data marts. Any authorized user can request a data mart with up to 250GB of storage by filling out a simple Web-based form. Within minutes of approval, the data mart is not only available, but it is populated with the appropriate data so the user(s) can begin working with it immediately. The collaborative aspect, referred to as eBay DataHub, allows users to publish any analysis from MicroStrategy or Tableau BI applications with the click of a button. Users can comment on these, follow each other, follow different topics, join analytical groups and participate in discussions – think LinkedIn for analytics. DataHub provides a centralized place to create and monitor all analytical activity a user might be involved in.
I’ve seen other aspects of collaborative BI previously. For instance, I commented on the collaborative aspects of IBM Cognos 10 which support collaborative discussion of decision-making processes and data lineage. I also like the way salesforce.com’s Chatter can be used to embed analytic dashboard objects directly into a chat stream. However, both of these examples were vendor-driven demonstrations. No longer just an ivory tower exercise or a twinkle in a software developer’s eye, the examples of eBay and Boeing show that collaboration can provide value to enterprise BI.
Consumerization has impacted mobile BI by bringing more mobile devices into the enterprise. Similarly, social media is impacting BI by bringing tools as well as knowledge of collaboration into the enterprise. We’ve tried for years to create a collaborative environment for BI using notes, annotations, workflow and email as a poor man’s substitute. With tools like Facebook and Twitter in the hands of consumers and with tools like salesforce.com Chatter and Tibco tibbr facilitating enterprise collaboration, perhaps we’re on the verge of a breakthrough in collaborative BI.
Ratzesberger mentioned that eBay is considering making the code behind DataHub open source. I hope it chooses that route because it would provide a great starting point for others to begin to think about or embrace collaborative BI.