A few weeks back I was at the National (Indian) Software Products' conclave at Bangalore. There were a lot of startups that were present. The buzz was amazing (in no small measure due to the presence of Guy Kawasaki and Naeem Zafar). I was able to interact with a lot of startups (good opportunity enabled via the Startups Track that I was co-organizing at the conclave). Among many others, there were two startups that were particularly interesting and both were looking at RDF (the Web3.0 Semantic Web markup standard) use cases in Enterprise solutions - particularly for knowledge management and data mining.
Now coming to think of it, the Web3.0 approach to a semantic web also makes a lot of sense to enterprise data. Both for Intranet content and for business data. For the Intranet, this enables creating a usable 'knowledge' veneer on the static content, wikis, discussion forums and other myriad information sources in enterprise Intranets. A veneer that allows creating semantic linkages and references across these various information sources. And for business data, it will enable creating semantic linkages across business data.
Coincidentally, I came across this article (few years old) on the 'Semantic Integration' of Enterprise reporting data; the data warehouses. Here the emphasis is on SVT (Single Version of Truth), and it recommends having just one data warehouse as the master. Now wouldn't it be nice to extend the paradigm to enterprise data as well? Meaning... the OLTP database is itself the DW as well. This is not entirely unfounded. Informix, the 2nd largest UNIX DB in the 1990s (and since extinct), actually attempted this. They built DW capabilities into the OLTP database, thereby attempting to eliminate the need to have two separate databases.
While a single DB is not possible, an integrated view of the enterprise data that collates all sources is not far fetched. In fact, SI actually enables it today. The data exchanges between various applications in the enterprise is a need and reality of today - even more so in the integrated enterprise with extensive use of SOA infrastructure. To this you can add Master Data management. Now while solutions like SI do enable a transparent access to various data sources in the enterprise with all semantics of the same modeled and preserved to present a common enterprise view of all data in the enterprise, wouldn't it be nice to extend the same further?
Consider this... with the semantics of various data sources mapped to a common enterprise view, this could be extended to allow dynamic ad hoc querying. And if this is also marked up with RDF meta data that provides linkages across applications, this will also allow semantic querying in Web 3.0 languages like Sparql. Extending this further, one could also look at getting semantic results collating this enterprise results with even sources on the web. For example: this could enable getting results for queries searching all customers that have bought high-value products from the enterprise and have CEOs that are interested in sailing. Now the list of customers is available in the CRM & Order processing system. But the information on who the CEO is may not be in the enterprise DB - this may be on the client companies website. And the fact that the CEO likes sailing may be on a social networking site. Now Web 3.0 will integrate the company site with social networking site and enable this linkage that the CEO likes sailing. And if we enable RDF within the enterprise, then that will enable the full query to find the "customers that have CEOS who like sailing".
At this point, the use case is more academic. (And some work is underway at IIIT-H). But in few years as RDF gets traction and Web3.0 usage picks up, the need for integrating enterprise data also into this semantic search space may follow. And when this occurs, the enterprise model based data integration that DXSI enables will be a strong starting point for such solutions.
View all posts from Ramesh Loganathan on the Progress blog. Connect with us about all things application development and deployment, data integration and digital business.
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