IS500: Information Systems Instructor: Dr. Boris Jukic

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IS500 Information Systems Instructor Dr. Boris
Jukic

• Decision Support Systems

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Systems and Technologies that Support
Organizational Decision Making

• Decision-enabling, problem-solving, and
  opportunity-seizing systems

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Why are Decision Support Systems back in Vogue?

• The amount of information people must understand
  to make decisions, solve problems, and find
  opportunities is growing exponentially

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Executive information Systems

• Executive information system (EIS) a
  specialized DSS that supports senior level
  executives within the organization
• Most EISs offering the following capabilities
• Consolidation involves the aggregation of
  information and features simple roll-ups to
  complex groupings of interrelated information
• Drill-down enables users to get details, and
  details of details, of information
• Slice-and-dice looks at information from
  different perspectives

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EXECUTIVE INFORMATION SYSTEMS

• Digital dashboard integrates information from
  multiple components and present it in a unified
  display

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Artificial intelligence (AI)

• Intelligent systems various commercial
  applications of artificial intelligence
• Artificial intelligence (AI) simulates human
  intelligence such as the ability to reason and
  learn and typically can
• Learn or understand from experience
• Make sense of ambiguous or contradictory
  information
• Use reasoning to solve problems and make
  decisions
• AI Fell out of favor in the early 90s
• Back in Fashion?

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Artificial intelligence (AI)

• The three most common categories of AI include
• Expert systems computerized advisory programs
  that imitate the reasoning processes of experts
  in solving difficult problems
• Neural Networks attempts to emulate the way the
  human brain works
• Intelligent agents special-purposed
  knowledge-based information system that
  accomplishes specific tasks on behalf of its
  users
• Common example shopping bot

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Data Mining

• Common forms of data-mining analysis capabilities
  include
• Cluster analysis
• Association detection
• Statistical analysis

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Cluster Analysis

• Cluster analysis a technique used to divide an
  information set into mutually exclusive groups
  such that the members of each group are as close
  together as possible to one another and the
  different groups are as far apart as possible
• CRM systems depend on cluster analysis to segment
  customer information and identify behavioral
  traits

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Association Detection

• Association detection reveals the degree to
  which variables are related and the nature and
  frequency of these relationships in the
  information
• Market basket analysis analyzes such items as
  Web sites and checkout scanner information to
  detect customers buying behavior and predict
  future behavior by identifying affinities among
  customers choices of products and services
• Beer-Diapers example

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Statistical Analysis

• Statistical analysis performs such functions as
  information correlations, distributions,
  calculations, and variance analysis
• Forecasts predictions made on the basis of
  time-series information
• Time-series information time-stamped
  information collected at a particular frequency

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Data Warehouse Definition

• Data Warehouse An enterprise-wide structured
  repository of subject-oriented, time-variant,
  historical data used for information retrieval
  and decision support. The data warehouse stores
  atomic and summary data.(Bill Inmon, paraphrased
  by Oracle Data Warehouse Method)

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Need for Data Warehousing

• Integrated, company-wide view of high-quality
  information.
• Separation of operational and analytical systems
  and data.

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OPERATIONAL vs. ANALYTICAL DATA

• Operational Data Analytical Data
• Data Differences
• Typical Time-Horizon Days/Months Typical
  Time-Horizon Years
• Detailed Summarized (and/or Detailed)
• Current Values over time (Snapshots)
• Technical Differences
• Can be Updated Read (and Append) Only
• Control of Update Major Issue Control of
  Update No Issue
• Small Amounts used in a Process Large Amounts
  used in a Process
• Non-Redundant Redundancy not an Issue
• High frequency of Access Low/Modest frequency
  of Access
• Purpose Differences
• For Clerical Community For Managerial
  Community
• Supports Day-to-Day Operations Supports
  Managerial Needs
• Application Oriented Subject Oriented

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OPERATIONAL vs. ANALYTICAL DATA
Hardware Utilization(Frequency of Access)
Operational Data Warehouse