Business Intelligence

DSS

 

Chair(s): Benjamin B. M. Shao (ben.shao@asu.edu) and Robert D. St. Louis (ST.LOUIS@asu.edu)
University Affiliation: Arizona State University
Phone: (480)727-6790
SIG URL:

Description:

The goal of business intelligence (BI) is to summarize massive amounts of disparate corporate data into succinct information that can help managers better understand their business processes, make informed decisions, and improve organizational efficiency. BI, for example, gives managers the ability to amalgamate enterprise-wide data into specific metrics that link customer service objectives to the performance of the sales force. In today’s strapped economy, accurate BI metrics are even more critical for measuring and managing business performance. Many technologies contribute to BI solutions, including databases, data warehouses, data marts, analytic processing, and data mining, among others. BI acquires data from multiple platforms and provides ubiquitous access. This presents numerous technical and managerial challenges. Among these challenges are data warehouse development methodologies, data consolidation from multiple sources, web integration, data visualization, real-time business metrics, data-mining applications, and issues related to securing and protecting data, infrastructure and the resulting intelligence. This mini-track aims to promote innovative research in these BI domains.

The mini-track will focus on:

  • Real-time business metrics (such as performance measurements)
  • Supporting the “balanced scorecard”
  • Using the warehouse to create “digital dashboards”
  • Data warehouse development
  • Data mart development
  • Critical success factors for data warehouse implementation
  • Data mining techniques (neural networks, genetic algorithms, decision trees)
  • Analytical processing
  • Customer profiling
  • Visualization techniques for enterprise data
  • Techniques for summarizing data
  • End user queries and query languages
  • Meta-data management
  • Integration of legacy data (transformation of data)
  • Assessing data warehouse performance
  • Considerations for the web-based data warehouse
  • Integration of web services with the data warehouse
  • Information extrication and report generation
  • Securing the enterprise-wide data store
  • Information assurance
  • Access control and intrusion detection
  • Protection of infrastructure, networks, and data warehouse

 

 

 AMCIS 2007 Colorado        http://www.biz.colostate.edu/amcis07/       Key Dates:

Paper Abstracts Due (optional) :  Monday, February 5, 2007
Papers Due:   Monday, March 5, 2007
Notification of Acceptance:   Monday, April 16, 2007
Camera Ready Copy Due:   Monday, April 30, 2007