************************************************************ DSS News D. J. Power, Editor August 18, 2002 -- Vol. 3, No. 17 A Bi-Weekly Publication of DSSResources.COM ************************************************************ Check Larry English's article "Ten mistakes to avoid if your data warehouse is to deliver quality information" ************************************************************ Featured: * DSS Wisdom * Ask Dan! - Is ETL software needed to build a model-driven DSS? * Report from AMCIS 2002 - Dallas * What's New at DSSResources.COM * DSS News Releases ************************************************************ DSS News is sent to more than 850 subscribers from 50 countries. Please forward this newsletter to people interested in Decision Support Systems and suggest they subscribe. ************************************************************ DSS Wisdom According to Graham Allison, the Cuban Missile Crisis and technology advances prompted a number of changes in military decision making. Allison writes "Advances in the technology of communications made it possible for political leaders in the White House to talk directly with commanders of destroyers stationed along the quarantine line. Advances in the technology of mass destruction created the possibility that acts by men on a single destroyer in that quarantine line could rapidly escalate to bring death to millions of Americans. Thus the governmental leaders had both the capability and the incentive to reach out beyond the traditional limits of their control. Maps in the 'Situation Room' in the basement of the White House tracked the movement of all Soviet ships. The members of the ExCom knew each of the ships by name and argued extensively about which should be stopped first, at what point, and how. Sorenson records 'the President's personal direction of the quarantine's operation ... his determination not to let needless incidents or reckless subordinates escalate so dangerous and delicate a crisis beyond control.' Thus, for the first time in U.S. military history, local commanders received repeated orders about the details of their military operation directly from political leaders -- contrary to two sacred military doctrines. This circumvention of the chain of command and the accompanying countermand of the autonomy of local commanders created enormous pain and surface friction. (p. 127-128)" from Allison, G. T., Essence of Decision: Explaining the Cuban Missile Crisis, Boston, MA: Little, Brown and Co, 1971. ************************************************************ Get Dan Power's new book, Decision Support Systems: Concepts and Resources for Managers, at http://greenwood.com/books/BookDetail.asp?dept_id=1&sku=Q497. ************************************************************ Ask Dan! by Daniel J. Power Is ETL software needed to build a model-driven DSS? Extract, transform and load (ETL) tasks are part of building many types of DSS, including some model-driven DSS. BUT, the ETL software developed for creating and refreshing large data stores from transaction, enterprise resources planning (ERP) and/or operating systems is NOT needed for model-driven DSS. In the Ask Dan! column titled "What is ETL software and how is it related to DSS?" (DSS News 08/04/2002), the basics of this type of software are discussed. The article by Larry English published at DSSResources.COM on August 11, 2002 also has a discussion of ETL and data quality. This column trys to clarify what data is needed for model-driven DSS and how it is obtained. Model-driven DSS use complex financial, simulation, and/or optimization models to provide decision support. The needed data sets are usually small, and certainly much smaller than the 500 megabyte-5 terabyte data stores common with data-driven DSS. In some model-driven DSS, the user enters ALL of the data needed by the system. The DSS performs data validation and data storage. The data entry may be 5-15 parameter values, text or other inputs. No data is imported from a source system. For example, most of the model-driven decision aids at DSSResources.COM have users input all of the data required by the model. To try the Cost/Benefit Analysis decision aid designed by D. J. Power and programmed in javascript by A. P. Power, check URL http://dssresources.com/decisionaids/cbanalysis.html. In other model-driven DSS, a time series of data on one or more variables needs to be imported into the DSS. The data set may be 1000 to even 10,000 values. It is common to perform extract and transform tasks to create the data. A report or data set is exported from a source system. Then because the data set is small the data is usually cleaned up and formatted in a text editor or in a desktop application like Excel. Excel is often a useful tool for creating small data sets for use with a model-driven DSS. The data set can then be incorporated into a spreadsheet-based DSS built using Excel or Lotus 123 or imported into another DSS development environment. Larger data sets are used for some specialized model-driven DSS, but the size of the data set remains modest compared to data marts and data warehouses. For example, Radical Logistics sells transportation software for calculating distances and rates. Data on "thousands of shipments" is used for the analysis and the data needs to be verified and cleaned up for correct ZIP codes and mileages. The Radical Logistics software help with ETL, analysis and decision support. Another common type of model-driven DSS uses a small number of data values from an external database that is needed for the analysis by the DSS user. The user defines the analysis and inputs some parameter values. For example, many model-driven investment DSS extract data from a historical stock market database. The Intrinsic Value per Share Calculator at Quicken.com extracts earnings and price information from a general purpose database of stock information and the user inputs assumptions about interest rates for "What if?" analysis. Finally, some model-driven DSS need very large data sets to create a visual simualation that the DSS user can interact with. These data sets are created and data may be imported from video files, maps and other sources. For example, DaimlerChrysler has a Virtual Reality Center to analyze and understand digital models and simulation results. The data used is not ERP or transaction data. The extract, transform and load tasks are very different from those associated with data warehousing, business intelligence and data-driven DSS. So ... As the data needs of a model or models in a model-driven DSS increases, it becomes more likely that specialized software will be needed to help the DSS developer create the specific decision support data store. The software used to extract, transform and load the data depends on the data, the DSS development environment and the preferences of the developer. References English, L. P., "Ten mistakes to avoid if your data warehouse is to deliver quality information", DSSResources.COM, 08/11/2002. Power, D. J. "What is ETL software and how is it related to DSS?", DSS News, 08/04/2002. ************************************************************ Report from AMCIS 2002 - Dallas by Dan Power Chair, AIS SIG DSS AMCIS 2002 in Dallas had over 125 sessions. More than 300 papers were presented and there were 17 panels and tutorials. The SIG DSS business meeting was well attended and membership forms for SIG DSS should be available in September. Contact SIG DSS secretary/treasurer Ramesh Sharda, sharda@okstate.edu. So what were the highlights? Well ... the sessions on decision support and data warehousing! Keith Lindsey and Mark Frolick (Univ. of Memphis) discussed current issues in Data Warehousing. Cliff Ragsdale (Virginia Tech) chaired a panel on "Spreadsheet-based DSS Curriculum Issues". Cliff provided examples of how he uses spreadsheets and Visual Basic for Applications to teach DSS concepts. Paul Bergey (NC State) and I also discussed our teaching approaches. A session on Web-based DSS identified some interesting issues. In the final DSS paper session on Sunday morning, Steve Alter and Roger Pick presented different views of DSS. Alter presented a work system view of DSS that stimulated an interesting discussion and comments. I heard positive comments on a number of other sessions, but my highlights reflect only those sessions I could attend. Thanks to the mini-track co-chairs for DSS - H. Bhargava, D. Power, M. Warkentin, and for data warehousing - K. Dowling, D. Schuff, and R. St. Louis. The Tex-Mex Fiesta on Saturday night was "big" even by Texas standards. I'm sorry to report however, my opportunities to meet and chat weren't as frequent as in Boston last year. Perhaps that will change next year. Plans are in the works for AMCIS 2003, August 4-6, 2003 in Tampa, FL. The conference theme is "Navigating the Torrents of Technology". See you in Tampa. ************************************************************ What's New at DSSResources.COM 08/11/2002 Posted article by English, L. "Ten mistakes to avoid if your data warehouse is to deliver quality information", DSSResources.COM, 08/11/2002, URL http://dssresources.com/papers/dssarticles.html. ************************************************************ DSS News Releases - August 5 to August 15, 2002 Complete news releases can be found at DSSResources.COM. 08/15/2002 A.D.A.M., Inc. and Subimo partner to create comprehensive health care decision tools for consumers. 08/13/2002 Comshare(R) and Symmetry offer risk-free program to evaluate analysis services. 08/12/2002 Radical Logistics has rapid adoption rate for new transportation modeling solution. 08/08/2002 Intergraph's research program encourages innovation in the geosciences. 08/08/2002 Roche Italy selects MicroStrategy Business Intelligence Platform. 08/08/2002 Reminder: Americas Conference on Information Systems 2002 in Dallas, TX August 9-11, 2002. 08/07/2002 Plumtree offers $75,000 portal package. 08/07/2002 Managers are unable to communicate value ... and it costs their shareholders big-time. 08/06/2002 Hospitals reduce medical errors and improve care with handheld technologies. 08/06/2002 New business planning products challenge investment doldrums. 08/05/2002 Reminder: The Data Warehousing Institute World Conference, Las Vegas, NV, August 18-23, 2002. 08/05/2002 Primus Knowledge Solutions announces PrimusĀ® Quick Resolve - A new product that accelerates the productivity of tier-one agents. ************************************************************ You can read 786 DSS News releases in the Subscriber Zone at DSSResources.COM. ************************************************************ DSS News is copyrighted (c) 2002 by D. J. Power. Please send your questions to daniel.power@dssresources.com. |