As social computing matures, we see signs of a socialization of BI: Incorporation of social-media analysis into the BI toolkit, adaptation of social styles to BI processes, and development of BI tools that play nice on social platforms.
... with examples from TIBCO, JackBe, Tableau, IBM, and Lyzasoft
A country like Venezuela or Mexico socializes its oil companies to control the companies and ensure that profits flow to the state. Parents and schools socialize children, teaching them to play and interact well with others. Trending IT socialization -- corporate embrace of social platforms and approaches -- weaves elements of both threads. As social computing matures, we see, in particular, signs of a socialization of BI: Incorporation of social-media analysis into the BI toolkit and social data into BI analyses, adaptation of social styles to BI processes, and development of BI tools that play nice on social platforms. I'll tackle points 2 and 3 today and the first point in a later article.First, sharing
TIBCO says its recently released Spotfire Silver is "more than traditional BI in a SaaS offering; it is essentially a 'social BI' offering." Personally, I think it takes more than Spotfire Silver's ability to "[allow] users to embed live dashboards into their business blogs and online articles" to create social BI. Social is about sharing, yes, but it's also effectively about collaboration and supporting -- even encouraging -- adaptive reuse without unnecessary constraints.
Adaptive reuse without unnecessary constraints is what you get via enterprise mash-ups, a laissez-faire permissive model that focuses on integration, composition, and also sharing, affording a high degree of flexibility. I'll point you to a short paper, Nimble Intelligence: Enterprise BI Mashup Best Practices, that I wrote for solution-provider JackBe. It explores these ideas.
Nonetheless, sharing is a significant first step. Tableau Software took that step with the launch of Tableau Public back in February. The software provides the ability, similar to but predating Spotfire Silver's, to Web-embed visual analytics. The company has published examples to a gallery site. Check out a couple of other, live examples:
I'd argue that if the TIBCO and Tableau offerings allow BI to be seen farther afield, they stand on the shoulders of a giant, in this instance, IBM. (The image to the right is Blind Orion Searching for the Rising Sun by Nicolas Poussin.) IBM's ManyEyes is a "shared visualization and discovery" system, a product of the company's Visual Communication Lab. It lets you upload data and generate a visualization using twenty different visualization types, or you can use a dataset that someone else uploaded. The goal is to "'democratize' visualization and to enable a new social kind of data analysis."
Next, social collaboration
BI tools that play nice on social platforms, tools that let you share your analyses to allow others to draw insights from them, are a first step. Collaborative BI is a second form of social BI. For this form of social BI, users need tools that support individual initiatives and then sharing and then allow teams to move beyond to collective work. Here social styles get baked into BI goals, methods, and software.
Open source software development, with distributed teams, decentralized management, and democratic-meritocratic contributions, foreshadowed this variety of social BI. At least one company is focusing on this approach, Lyzasoft.
Company founder Scott Davis seeks to translate business experiences into better solutions, a sort of bottom-up approach to creating BI tools and processes, and for him, better solutions involve "involve a deep blending of social-media tools and processes with those of BI." His response to my request for his definition of "social BI," relating the term to a Lyzasoft tagline:
"Collaborative Business Intelligence is a diverse intelligence community in which members of varying topical, integrative, analytical, promotional, and executive expertise can work in fluid, self-organizing teams to create, share, analyze, enrich, critique, rate, relate, modify, forward, and repurpose quantitative and qualitative information components in ways that make relevant information easier for everyone in the community to find, understand, and apply to decisions."
I see moves to incorporate social-media analysis into enterprise data analyses as a third aspect of a socialization of BI, but I'll need to save examination of this last of three points for my next blog article.
Social-data analysis and integration is the most challenging to realize of my three social-BI components, more complex than bringing collaborative processes to BI, far more difficult than sharing analyses via social-media BI embedding. Bringing social media into BI -- and from there, exploiting comprehensive BI insights to inform social-media strategy, or rather, coordinated, multi-channel strategy -- involves text analytics for robust, beyond-keywords social-media monitoring and for information extraction, it involves meeting thorny data cleansing and record-linkage (integration) challenges, and it involves studying not only content but also the networks of individuals and organizations, across social and enterprise platforms, across which people interact and messages propagate.
I'm organizing a new conference, Smart Content: The Content Analytics Conference, slated for October 19, 2010 in New York. Smart Content, as the conference Web site explains, will explore business challenges, technologies, and solutions in content analytics, the world where content management & publishing, search, and analytics intersect. The conference is about digital transformation, about enhancing the business value of information, both enterprise content and social media.
If you've gotten this far -- if the Socialization of BI topic captured your interest, there's a good change you'd find Smart Content worth attending. And if you're so inclined, you may submit a speaking proposal -- a full presentation or a 5-minute lightning talk on research or a product -- via a form on the conference site.As social computing matures, we see signs of a socialization of BI: Incorporation of social-media analysis into the BI toolkit, adaptation of social styles to BI processes, and development of BI tools that play nice on social platforms.
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