Blog: Dan Power

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Tactical Data-Driven DSS

Insights into Action is the theme of this year's Teradata Partners User Group Conference. The conference started for me on Sunday, October 7. It was a busy day with a workshop from 8am-12:30pm conducted by Stephen Brobst, Chief Technology Officer of Teradata on Active Data Warehouse Deployment. Stephen's workshop was a great blend of strategic concepts and technical issues associated with building and deploying tactical DSS.

This morning Michael Koehler, President and CEO of Teradata, reminded an opening session audience of approximately 3000 that Teradata was the first database product designed especially for decision support.

According to the new slogan, Teradata is "focused on raising intelligence through data warehousing and enterprise analytics". The reality is that Teradata provides an array of products that can help information Technology staff build and deploy strategic and tactical data-driven decision support systems.

Until about 1999, users of data warehouses and data-driven DSS focused on periodic reporting, ad hoc queries, strategic analyses and creating decision support special studies. Today once the data warehouse infrastructure is in place and a need is established, we can build and deploy data-driven DSS that assist in frontline, operations decision making and real-time performance monitoring.

Brobst draws a distinction between Online Transaction Processing (OLTP) systems, traditional DSS and tactical DSS. What I call tactical data-driven DSS have many characteristics that are similar to OLTP as far as systems performance, flexibility of queries, systems availability, update frequency, query type and indexing. The major difference is the contrasting purposes of OLTP and tactical data-driven DSS, i.e. recordkeeping/bookkeeping versus supporting operations decision making. A tactical data-driven DSS will also have more integrated data, historical data as well as current OLTP-like data.

This blog isn't the right format to explain tactical data-driven DSS, but perhaps in a future article or column I can expand on the concept. The conclusion is clear -- the technologies are available today to build sophisticated data-driven DSS to support business logistics decisions, customer service decisions, inventory management decisions and many other operations decisions that can benefit from current, timely facts.

I'll prepare a trip report on Teradata Partners for the next issue of DSS News that will be published Oct. 21, 2007. Yesterday's DSS News included my column titled "What are common DSS architectural patterns or styles?"

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