In previous posts of mine (here and here) I introduced our vision of Identity Analytics and the focus and purposes of our R&D activities.
I received a few emails and queries asking to clarify the link between Identity Analytics and Unstructured Data, considering that this was mentioned in the “On Identity Analytics: Setting the Context” HPL Technical Report.
We believe that “Unstructured Data” is a possible, fertile and rich “case study”/scenario where to explore the concept of Identity Analytics, the applicability of our approach and potential limitations..
The adoption of new “web 2.0” collaborative tools within organizations (TWiki, Sharepoint, IM, etc.) and social networks (Facebook, LinkedIn, del.icio.us, etc.) provides users with better ways to collaborate, create and share contents. At the same time this poses new threats and security risks, due to the nature of unstructured data, the fact that confidentiality issues could emerge from aggregated, simpler pieces of information and the difficulty to retain control on this data. This is where traditional Identity management solutions can show their limitations and where decision makers need to better understand the implications of their choices and/or the impact of defining new policies.
Our R&D work in Identity Analytics really aims, in this context, to explore how modeling and simulation can help to explain and predict the impact of some of these decisions on the organizations (e.g. in terms of risks, reputation, costs, etc.) and explore options and “trade-offs” by providing “what-if” analysis.
Of course the “unstructured data” scenario is just one of the various scenarios we are exploring. I would be interested in hearing from you about other areas you think the “Identity Analytics” approach could provide help and/or address (decision support) issues you might have.
--- NOTE: my original HP blog can be found here ---
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