Chapter 1: Data, Information, and Decision

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Chapter 1 Data, Information, and Decision

• Instructor Paul K Chen

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Topics

• Data, Information, and Decision
• Information System Categories
• System Analysis and Design What is it?
• Roles of System Analysts
• System Development Life Cycle A brief overview

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Topics

• CASE Tools What, Why? Categories
• Reengineering What and Types
• Object-Oriented Analysis and Design To be
  discussed in Chapter 22
• Decision Support System Data Warehousing

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Information as A Competitive Weapon

• Information technology and quality information
  are not
• the goals, but merely to support organizations to
  reach
• goals of
• Superior products and services
• Greater productivity
• Eventually success

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Data, Information, and Decision

• Data
• Information (Data Process)
• Knowledge
• Decision (Information
• Knowledge)
• Data/Information/Decision

• Data Resource Management (DRM)
• MIS (OLTP) OOAD
• KM (Knowledge Mgt), KWS (Knowledge Work Systems)
• DSS ESS, EIS (Executive Level)
• GDSS, CSCW
• Data Warehousing/Data Mart/Data Mining/OLAP
  (Executive, Collaborative and individual
• levels)

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Data, Information, and Decision

• Data Data
  processing
• Processing System
  Analysis/Design
• Information MIS, Database
  Systems
• Object (DataProcessing) Object-Oriented SD/DA
• Knowledge Artificial
  Intelligence
• Information Expert
  system
• Decision (executive level) DSS, EIS
• Decision (all levels, sophisticated) Data
  warehousing
• 
  Data Mining

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DRM (Data Resource Management)

•   Definition
•   Data resource management (DRM) is the
  business discipline which focuses on how data
  can be managed to most efficiently support the
  business enterprise. DRM addresses the
  management of all enterprise data. When combined
  with other enterprise processes, DRM provides
  information when needed, where needed, in the
  form needed, with desired accuracy and at minimum
  cost for business enterprise.

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DRM Why?

• Data resource management becomes increasingly
  critical
• to the success of the corporation in the
  marketplace due to
• these new realities
•      
• The competitive, global environment that business
  is facing
• Explosive growth of the web over the internet
• Increasing use of data warehouse systems to make
  better decisions
• Business intelligence dependent on reliable
  information (data)

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DRM What?

• Providing a unified and integrated approach for
  planning, control and integration of our data
  assets in support of enterprises business
• Encouraging the reduction of unnecessary data
  duplication
• Encouraging the reuse and sharing of high quality
  data
•  
• Done right, the investment can be paid back
  many times over.

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DRM Approaches-How

• Understanding data structure via data modeling
  A comprehensive data resource model is mandatory
  to properly manage and design the data resource.
• Deploying strategies for managing data server
• infrastructure
• Standardizing the use of tools and procedures
• Designating data stewardship

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XML (Extensible Markup Language)for Data
Management

• Quickly becoming de facto standard for the
  sharing of information in the e-business arena.
• Proven itself extremely versatile and highly
  qualified for data exchange, interoperability,
  and integration.
• Enabling legacy data from relational databases
  and other files to be migrated into future
  applications.
• Integrating the structured data with unstructured
  data in text documents, reports, email, graphics
  and images, audio and video files to present the
  new applications.

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Information System Categories

• TPS (Transaction process systems)
• OAS (Office automation systems)
• KWS (Knowledge work systems)
•  
• MIS (Management information systems)
• DSS (Decision support systems)

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Information System Categories

• ESS (Executive support systems)
• GDSS (Group decision support systems)
• CSCW (Computer supported collaborative systems)
  
•  
• Data Warehousing, Data Mart, Data Mining(OLAP
  Online Analytical Processing)

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Information System Categories--e-Business

• CRM (Customer Relationship Management)
• ERP (Enterprise Resource Planning)
• SCM (Supply Chain Management)
• EAI ( Enterprise Application Integration)

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System Analysis and Design What is it?

• System Analysis and Design is a systematic
  approach to identifying problems, opportunities,
  and objectives, analyzing the information flows
  in organizations designing computerized
  information systems to solve a problem.

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Roles of System Analysts

• Systems analysts act as outside consultants to
  business, as supporting experts within a
  business,
• and as change agents.
• Analysts are problem solvers, and require
  communication skills
• Its important for analysts to be aware of their
  ethical framework as they work to build
  relationships with users and customers.

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System Development Life Cycle A brief overview

• It is a systematic approach to solving business
• problem. Its divided into seven phases
• Identifying problems, opportunities, and
  objectives
• Determining system requirements
• Analyzing system needs
• Designing the recommended systems
• Developing and documenting software
• Testing and maintaining the system
• Implementing and evaluating the systems

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System Development Life Cycle A brief overview

• Why should a system development project be
• segmented in phases?
• Project Management easier to understand and
  manage its deliverables and track its progress
• Resources Better utilize the resources related
  to
• technology, skills, and time
• Risk Minimize commitment and cost in case the
  project restarts.

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CASE Tools What, Why? And Categories

• What?
• CASE (Computer-aided Software Engineering)
• CASE is not just a technology or class of
  products but a
• problem-solving approach, a set of methods and
• disciplines, maybe even a philosophy that guides
  software
• development toward a real engineering discipline.
  

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CASE Tools What, Why? And Categories

• Why?
• To improve analyst productivity
• To facilitate communication among users and
  analysts
• To provide continuity between life cycle phases
• To assess the impact of maintenance

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CASE Tools What, Why?And Categories

• CASE tools categorized relative to project
  lifecycle
• Front-end products (Upper CASE) focus on the
  strategic planning, analysis and logical design
  phases
• Back-end products (Lower CASE) emphasize
  physical design and construction

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3 Rs of Software Engineering

• What? Take a guess.

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3 Rs of Software Engineering

• Reusability
• Re-engineering
• Reverse-engineering

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Reusability What? Characteristics

• When we speak of reuse in software engineering,
  we mean everything that can be reused at a later
  time. This includes all the information and
  knowledge that has been developed, system
  architectures and development methods.
• Normally we talk about reuse, we focus on
  component. A component is a standard building
  unit in an organization that is used to develop
  applications.

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Reusability What? Characteristics

• Components are characterized by
• A high quality product due to careful design and
  testing.
• Not bond to any specific application
• Packages for reuse with a well-designed
  interface, documentation, etc.
• General so that it can be used in several places.
• Components such as Use cases, classes,
  framework,
• subsystems, interfaces.

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Reengineering What? and Types

• Business reengineering is the fundamental
  rethinking and radical redesign of business
  processes and product to achieve dramatic
  improvements in critical measure of performance,
  such as cost, quality, capital, services and so
  on.

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Reengineering What? and Types

• Product Reengineering
• Process Reengineering
• Total quality management
• Just-in-time mfg
• E-business and E-Commerce
• Data Warehousing, OLAP, Data Mining

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Ways to Improve Process

• People Teams, Experience
• Tools Testing and Development Tools
• Techniques Modeling Prototyping
• Physical Environment Workflow, Procedures

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Decision Support System Data Warehousing

• Characteristics
• 1. A central database that is loaded from
  
• multiple operational databases for the
  
• purpose of end-user access and decision
  
• support.

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What is a Data Warehouse? - Continued

• 2. A data warehouse differs from an
• operational system in that the data it
• contains is normally static and updated
• in a scheduled manner through massive
• loading procedures.

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What is a Data Warehouse? - Continued

• 3. A data warehouse is developed to
• accommodate random, ad hoc queries
• and to allow users to drill down to
• minute levels of detail.

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Definition

• Bill Inmon defines a central data warehouse as a
  
• database that is
•  
• 1. Subject Oriented
• Data naturally congregates around major
  categories within any corporation. These
  categories are called subject areas. For example,
  subject areas are bill of material, customer,
  product, and criminal profile. The subject area
  will be designed to contain only the data
  appropriate for decision support analysis.

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Definition - Continued

• 2. Integrated
• Data integration is displayed by consistence
• in the measurement of variables, naming
• conventions, physical data definitions
• across the data. There will be only one
• definition, identifier, etc., for each
  subject
• area.

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Definition - Continued

• 3. Time Variant
• Data in the DW is historical and accurate as
  of some point in time. Since DW data is extracted
  from operational systems, it must have an element
  of time as part of its key structure

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Definition - Continued

• 4. Static
• Since the data in DW is a snap shot extracted
  
• from operational system, it must be static or
  
• non-updateable.

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The Benefits of Data Warehouse

• Enable workers to make better and wiser decisions
  
• A data warehouse is specifically developed to
  allow users the ability to explore data in an
  unlimited number of ways, accommodating
  essentially any query a manager could dream up
  and providing access to the data sources that are
  behind the results. For example, information
  gleaned from a data warehouse can change pricing
  information.

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The Benefits of Data Warehouse

• Identify hidden business opportunities
• A data warehouse performs a second, and very
  valuable function by searching data for trends
  and abnormalities which users may not know to
  look for.
• For example Assisting companies in spotting
  sales trends, and detecting erroneous or
  fraudulent billings.

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The Benefits of Data Warehouse

• Bending with the customer
• A data warehouse can help companies by really
  understanding who their customers are and what
  services they are using.
• For example, by collecting and analyzing
  internet portal click stream data, companies are
  able to build extensive user profiles to boost
  profits through sales channel.

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The Benefits of Data Warehouse

• Precision Marketing
• A data warehouse can aid in detecting
  segments of the marketplace (geographically and
  demographically) which remain untapped, and help
  show the best way to reach out to these potential
  customers (rapid response to market and
  technology trends).

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OLTP vs. Data Warehousing
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Typical Data Warehouse Queries- A National Real
Estate Agent Case

• Which type of property sells for prices above the
  average selling price for properties in the main
  cities of USA and how does this correlate to
  demographic data?
• What are the three most popular areas in each
  city for renting property in 1997 and how does
  this compare with the figures for the previous
  two years?
• What is the current monthly revenue for property
  sales at each branch office, compared with
  rolling 12-monthly prior figures?
• What is the relationship between the total annual
  revenue generated by each branch office and the
  total number of sales staff assigned to each
  branch office?

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Typical Architecture of a Data Warehouse
Information
decision
data