Hearst also notes the growing importance of social search, in collaboration, crowdsourcing and basic social communication. This is a topic I'm currently developing in a new White Paper with Lyzasoft and to which I'll return in a future post.
The final point that Hearst makes is on the emergence of video as a means of communication, replacing text-based approaches among some younger users of the Web. This poses some significant challenges for both search and analytics in the future. In recent years, text analytics has become an important tool for sentiment analysis and so on. "Video analytics" is still in its infancy.
Returning to NeutrinoBI, let's take a look at the exciting concept of freeform search. Freeform search, in one sentence, enables Google-like search of highly-structured information as is found in data warehouses and data marts. The secret of moving from keyword search of content to freeform search lies in understanding and representing the structure of relational data in a way that supports intelligent parsing of free text searches. This structure originates in data modeling and is carried into relational database design and associated metadata--which columns occur in which tables, identification of primary and secondary keys and foreign-key relationships between tables. Structuring, whether into normalized or multidimensional schemata, also constrains allowable values in certain columns and relationships between them.
The result is a conceptual hierarchical structure that is hardwired in the database or application in the multidimensional approach. For example, geographical location is often expressed in the form of regions, which are comprised of countries, which are further comprised of states / provinces, which break down to counties, each of which contains a known and limited set of values. In the case of freeform search, a process known as hierarchical value decomposition is used to automatically analyze database structures and create the indexes and metadata--the information context, unique and specific to the structure and content of the underlying data--needed to extract meaning from the key words entered by the user at search time. The result is a system that can be easily used by business people in their own terminology and can be constructed rapidly and efficiently by IT. Further details can be found in my White Paper "Freedom from Facets: Discovering the data you really need".
On the Web, a search interface is already the norm. As Hearst describes, it is evolving into something closer to the way humans interact. What we see on the Web usually transfers into the enterprise environment. The function that NeutrinoBI is already delivering shows how these developments can be applied to BI and, in the process, is beginning to provide business users with a powerful, yet simple, way to get the information they need.
Posted November 30, 2011 5:10 AM
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