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Barry Devlin

As one of the founders of data warehousing back in the mid-1980s, a question I increasingly ask myself over 25 years later is: Are our prior architectural and design decisions still relevant in the light of today's business needs and technological advances? I'll pose this and related questions in this blog as I see industry announcements and changes in way businesses make decisions. I'd love to hear your answers and, indeed, questions in the same vein.

About the author >

Dr. Barry Devlin is among the foremost authorities in the world on business insight and data warehousing. He was responsible for the definition of IBM's data warehouse architecture in the mid '80s and authored the first paper on the topic in the IBM Systems Journal in 1988. He is a widely respected consultant and lecturer on this and related topics, and author of the comprehensive book Data Warehouse: From Architecture to Implementation.

Barry's interest today covers the wider field of a fully integrated business, covering informational, operational and collaborative environments and, in particular, how to present the end user with an holistic experience of the business through IT. These aims, and a growing conviction that the original data warehouse architecture struggles to meet modern business needs for near real-time business intelligence (BI) and support for big data, drove Barry’s latest book, Business unIntelligence: Insight and Innovation Beyond Analytics, now available in print and eBook editions.

Barry has worked in the IT industry for more than 30 years, mainly as a Distinguished Engineer for IBM in Dublin, Ireland. He is now founder and principal of 9sight Consulting, specializing in the human, organizational and IT implications and design of deep business insight solutions.

Editor's Note: Find more articles and resources in Barry's BeyeNETWORK Expert Channel and blog. Be sure to visit today!

data searching boy.pngI wrote a White Paper for an interesting, UK-based start-up, NeutrinoBI, back in October on the topic of freeform search in BI.  So, a new paper by Marti A. Hearst, "'Natural' Search User Interfaces", in the November issue of "Communications of the ACM" caught my attention.  I was particularly interested because Hearst has been one of the main proponents of faceted search, an approach that is relatively unsuccessful in BI.  I wondered if I had missed some new developments in the field.

In the event, Hearst's paper is somewhat futuristic.  Nonetheless, he makes some fascinating observations about how users' interaction with computers is undergoing significant change.  The first trend is a move towards voice interaction, driven in particular by smart phones.  There have been dramatic improvements in voice recognition over the past few years, and the ability of software to recognize and interpret simple commands allows users to speak more naturally.  This is driving a move away from single keyword or key phrase searches, even when typed into Google, for example.  However, more work is needed to enable reliable identification of context and the sequential inquiry approach often favored by users.  Natural language-like query has been a topic of ongoing interest in BI, and NeutrinoBI's product supports this in its query interface.  

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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