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MANAGEMENT INFORMATION SYSTEMS (MIS) LECTURE NOTES 4 SPRING 2010

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Title: MANAGEMENT INFORMATION SYSTEMS (MIS) LECTURE NOTES 4 SPRING 2010


1
MANAGEMENT INFORMATION SYSTEMS
(MIS)LECTURE NOTES 4SPRING 2010
  • FOUNDATIONS OF BUSINESS INTELLIGENT(DATABASES
    AND INFORMATION MANAGEMENT)

2
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • This lecture focuses on Data Management and how
    Businesses use Database
  • Technology to achieve their objectives.
  • When Businesses use Database Management Systems
    (DBMS) to organize their data, data get analyzed
    and the resulting information can be used to
  • Develop New businesses,
  • Achieve Operational Excellence,
  • Improve Management Decision Making,
  • Help the firm fulfil its Regulatory Reporting
    requirements.
  • Databases are the backbone or foundation of the
    business today and that most businesses would
    fail should their Databases cease to exist.

3
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • Database Knowledge is essential for several
    professions
  • If your career is in Information Technology
  • You will play a key role in providing Data
    Management Tools and expertise to
  • the firm.
  • You will be expected to Design Databases,
    implement and maintain Database Technology, and
    help promote Data Administration Policies and
    Procedures.
  • If your career is in Finance and Accounting
  • You will be using Databases to deal with
    Financial transactions such as Payments,
    Invoices, or Credit history. Or you will be
    working solidly with a massive Databases housing
    data about Security Stock prices , Investment
    Portfolios and Economic statistics.

4
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • If your career is in Sales and Marketing
  • You will be using Databases for tracking Customer
    orders, Analyzing Customer data for targeted
    Marketing campaigns, or identify profitable
    customers and products.
  • If your career is in Manufacturing Production, or
    Operations Management
  • You will be working with large Databases with
    data on raw materials, Finished goods in
    inventory , Suppliers, Product components.
    Product quality and goods in transit that can be
    used for Supply Chain Management.
  • If your Career is in Human Resources
  • You will be working with Databases maintaining
    data on Employees, Benefit plans, Compensation
    plans, Training programs, and Compliance with
    Governmental regulations on health, safety, and
    equal employment opportunity.

5
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • USING DATABASES TO IMPROVE BUSINESS PERFORMANCE
    AND DECISION MAKING
  • Businesses use Databases to
  • Keep track of basic transactions, such as Paying
    Suppliers, Processing
  • Orders, Keeping track of Customers,
    and Paying Employees etc .. .
  • Provide information that will help the company
    run the business more efficiently, by helping
    managers and employees make better decision.
  • In a large company with large Database Systems
    for separate Business
  • Functional areas such as Manufacturing and sales,
    special capabilities and tools
  • are required to analyze vast quantities of data
    and to access data from multiple
  • Systems.
  • Special capabilities such as Data Warehousing ,
    Data Mining, and Database Access tools can
    provide accessing facility to internal Databases
    via Web.

6
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA WAREHOUSES
  • Data Warehouse is a Database that stores both
    current and
  • historical data of potential interest to Decision
    Makers throughout
  • the firm.
  • Suppose that a Manager wants concise, reliable
    information about current operations, trends, and
    changes across the entire company.
  • Obtaining this information in a large company
    might be difficult because data are often
    maintained in separate Databases for specific
    Application Systems, such as Sales,
    Manufacturing, or Accounting Systems.
  • Moreover, some of the data may be in Sales
    Systems Database , and other pieces of data may
    be in the Manufacturing System Database.
  • Additionally, Systems may be Legacy Systems
    that use outdated DBMS Technologies or
    non-Database File Systems where information is
    difficult for users to access.

7
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA WAREHOUSES (Continued)
  • A Manager might have to spend a lot of time
    locating and gathering the needed data for
    decision making, or s/he may be forced to make
    decision based on incomplete knowledge.
  • Also, Manager might face with troubles if s/he
    wants to find data about past events since most
    firms only make the current data immediately
    available. - Data Warehousing address all of
    these problems.
  • The data originated in many Core Operational
    Transaction Systems, such as
  • Sales, Customer Accounts and Manufacturing, as
    well as data from
  • Web site transactions and from outside databases
    are consolidates and
  • standardize in a Data Warehouse.
  • As a result of Data Warehouse, information from
    different Operational Databases can be used
    across the Enterprise Management for Analysis
    and Decision making.

8
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA WAREHOUSES (Continued )
  • Data Warehouse makes the data available for
    anyone to access, as needed. However, data on
    Warehouse cannot be altered by the users.
  • A Data Warehouse System also provide a range of
    Ad-hoc and Standardized
  • Query tools, Analytical tools, and Graphic
    reporting facilities.
  • Many Companies use Intranet Portals to make
    the Data Warehouse Information widely available
    across the firm.

9
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA WAREHOUSE
  • Data Warehouse extracts current and historical
    data from multiple Internal
  • Operational Systems. This data is combined with
    data extracted from External sources
  • and reorganized into a Central Database designed
    for Management Reporting and
  • Analysis purpose.
  • The Information Directory provides Users with
    information about the available data.
  • the Warehouse.

10
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA MARTS
  • Companies often build Enterprise-wide Data
    Warehouses, where a Central Data
  • Warehouse serves the entire organization, or they
    create smaller, Decentralized
  • Warehouses called Data Marts.
  • A Data Mart is a subset of a Central Data
    Warehouse, in which a summarized
  • or highly focused portion of the organizations
    data is placed in a separate
  • Database for a specific Users population .
  • e.g. A company might develop Marketing and
    Sales Marts to deal with Customer
    information.
  • Data Mart typically focuses on a single Business
    area or line of business areas, so it can be
    constructed more rapidly and at lower cost than
    an Enterprise-wide Data Warehouse.

11
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • BUSINESS INTELLIGENCE TOOLS,
  • Data that have been captured and organized in
    Data Warehouses and Data
  • Marts, are available for further analysis.
  • A series of tools enables users to analyze the
    data to see new patterns, new
  • relationships, and insights that are useful
    for guiding Management Decision making.
  • These tools for consolidating, analyzing and
    providing Access to vast amounts of data to help
    Users make better business decisions are often
    referred to as Business Intelligence (BI).
  • The main Tools for Business Intelligence include
    -
  • Database Query and Reporting Software
  • Multidimensional Data Analysis Tools (Online
    Analytical Processing - OLAP)
  • Data Mining

12
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • BUSINESS INTELLIGENCE TOOLS
  • Business Intelligence tools provide firms with
    the capability to access mass
  • Information to
  • Develop knowledge about Customers, Competitors,
    and Internal
  • Operations
  • Change Decision making behaviour to achieve
    higher profitability
  • and other business goals.

13
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • BUSINESS INTELLIGENCE TOOLS
  • Firms Operational Databases keep track of the
    transactions generated as a
  • result of running the business.
  • Operational Databases feed data to the Warehouse.
    Managers use Business Intelligence tools to find
    patterns and meanings in the data.
  • Managers then act on what they have learned from
    analyzing the data by making more informed and
    intelligent business decisions.

14
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ONLINE ANALYTICAL PROCESSING (OLAP)
  • Online Analytical Processing (OLAP). Supports
    Multidimensional Data
  • Analysis, enabling users to view the same data in
    different ways using multiple
  • dimensions.
  • Each aspect of information such as - Product ,
    Cost, Pricing, Region, or Time period -
    represents a different dimension.
  • e.g. A Product Manager could use
    multidimensional Data Analysis tools to
    learn-
  • How many of a particular item were sold in
    Southeast region in March 2010
  • How that compares with the previous month and
    the previous March,
  • How it compares with the Sales Forecast.
  • OLAP enables users to obtain Online answers to
    Adhoc questions in very large Databases, such as
    Sales figures for multiple years.

15
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ONLINE ANALYTICAL PROCESSING (OLAP)

16
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ONLINE ANALYTICAL PROCESSING (OLAP)
  • The figure shows Multidimensional Model that
    could be created to represent say
  • Products, Regions, Actual Sales, and Projected
    Sales.
  • A Matrix of Actual Sales can be stacked on top of
    a matrix of projected sales to form a
  • cube with six faces.
  • If you rotate the cube 90 degrees again, you
    will see Region Versus Actual and Projected
  • Sales.
  • If you rotate 180 degrees from the original view
    you will see Projected Sales and
    Product versus Region.
  • Cubes can be nested within cubes to build complex
    views of data.
  • A company would use either a Specialized
    Multidimensional Database or a
  • Tool that creates Multidimensional views of Data
    in Relational DBMS.

17
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA MINING
  • Traditional Database Query answer such as
  • How many units of Product 403
    were shipped in March 2010?
  • OLAP supports much more complex requests for
    information such as
  • Compare Sales of Product 403
    relative to Plan by Quarter and Sales Region
  • for the past two years.
  • With both OLAP and Query-oriented Analysis, Users
    need to have a good idea about the information
    for which they are looking for.
  • Data Mining however is more discovery driven
  • Data Mining provides insight into corporate data
    that can not be obtained with OLAP or
    traditional Database Query
  • Data Mining finds hidden patterns and
    relationship in large Databases andInferring
    Rules from them to predict future behaviour.

18
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA MINING
  • The type of Information obtained from Data Mining
    include
  • Associations
  • Sequences
  • Classifications
  • Clusters
  • Forecasts
  • ASSOCIATIONS - Are occurrences linked to a
    single event.
  • E.g. A
    study of Supermarket Purchasing patterns might
    reveal that,

  • when Corn Chips are purchased, 65 of the
    time. a Cola drink is also
    purchased. But when
    there is a Promotion, cola drink is
    purchased 85
    of the time with Corn Chips/.
  • This
    information helps the Managers make better
    decisions because they
    have learned the profitability of
    a promotion.
  • SEQUENCES - Sequences of events are linked
    over time.
  • We might
    find for example, that if a House is purchased,
    65 of the time a
    new refrigerator will be purchased within
    two week , and 45 of the time
    an Oven will be bought
    within one month of the home purchase.

19
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA MINING
  • CLASSIFICATION - Recognizes patterns that
    describe the group to which an item

    belongs to. by examining existing items that
    have been

  • classified and by inferring a set of rules.
  • E.g Businesses
    such as Credit Card or Telephone companies worry
    about the loss of
    steady customers. The Classification helps
    discover the
    characteristics of Customers who are likely to
    leave and can provide a
    model to help managers predict those
    customers so that the
    Managers can devise special campaigns to
    retain such customers.
  • CLUSTERING Works in a manner similar to
    Classification when no groups have
    yet been defined. A Data Mining
    Tool can discover different
    groupings within data, such as finding
    affinity (similar) groups for
    Bank Cards or Partitioning a Database
    into groups of Customers
    based on demographics and types of
    personal investment.
  • FORECASTING Uses prediction in a different way
    than the others. It uses a series
    of existing values to forecast
    what other values will be.
  • e.g.
    Forecasting might find patterns in data to help
    managers

  • estimate the future value of continuous
    variables, such as Sales
    figures.

20
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA MINING
  • Associations, Sequences, Classifications,
    Clustering and Forecasting perform high-level
    Analyses on patterns or trends, but they can also
    Drill down to provide more detail when needed.
  • There are Data Mining Applications for all the
    Functional areas of business, and for government
    and scientific work. One popular use of Data
    Mining is to provide detailed Analyses of
    Patterns in Customer Data for One-to-One
    Marketing Campaigns or for identifying
    profitable customers.
  • Example - Virgin Mobile Australia uses a
    Data Warehouse and Data Mining to
    increase Customer loyalty and roll out new
    services.
  • The Data Warehouse consolidates data from its
    Enterprise Systems, Customer Relationship
    Management System, and Customer Billing Systems
    in a massive Database.
  • Data Mining has enabled Management to determine
    the demographic profile of new customers and
    relate it to the handsets they purchased.
  • It has also helped Management evaluate the
    performance of each store and point-of-sale
    campaign, Customer reactions to new products and
    services, customer attrition rates, and the
    revenue generated by each customer.

21
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • PREDICTIVE ANALYSIS
  • Predictive Analysis predicts the outcomes of
    events, such as the probability of a
  • customer willingness in responding to an offer on
    purchase a specific product.
  • Predictive Analysis uses the following factors
  • Data Mining Techniques
  • Historical data,
  • Assumptions about future conditions
  • Example Body Shop International Plc.,
    used Predictive Analysis with its
    Catalogue Database on their Web site, and
    Retail Store Customers to
    identify Customers who were more likely to make
    catalogue purchases.
  • This information helped
    the company build a more precious and
    targeted mailing list for its Catalogues,
    improving the response rate
    for catalogue mailing and Catalogue revenue.

22
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • Data Mining Technology can combine information
    from many diverse sources to create a detailed
    Data Image about each of us our income, our
    driving habits , our hobbies , our families, and
    our political interests, within the privacy
    protection law!.
  • Thus, Data Mining is both a powerful and
    profitable tool, but it poses challenges to the
    protection of individual privacy.

23
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATABASES AND THE WEB
  • Many companies now use the Web to make some of
    the information in their internal
  • Databases available to Customers and business
    partners.
  • A Customer with a Web Browser can search an
    online Retailers Database for pricinginformation
    .
  • The Customer as shown in the figure below, access
    the Retailers Web site over the Internet using
    Browser software to request pricing data from the
    Retailer organizations Database, using HTML or
    XML commands to communicate with the Web Server.
  • Users access an organizations Internal Database
    through the Web using PCs and
  • Web Browser Software.

24
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATABASES AND THE WEB
  • Since many Back-end Databases cannot interpret
    commands written in
  • HTML, the Web Server passes these requests
    for data to software that translates HTML
    commands into SQL so that they can be processed
    by the DBMS.
  • In a Client/Server Architecture environment, the
    DBMS resides on a dedicated Computer called
    Database Server. The DBMS receives the SQL
    requests and Returns the required data.
  • The Middleware transfers information from the
    Organizations internal
  • Databases back to the Web Server for
    delivery in the form of a Web page to
  • the Customer.

25
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATABASES AND THE WEB
  • The Application Server software handles all
    application operations, including
  • Transaction Processing and Data access, between
    browser-based computers (PC)
  • and the companys back-end business applications
    or Databases.
  • The Application Server takes requests from the
    Web Server , runs the business logic to process
    transactions based on the request, and provides
    connectivity to the organizations back-end
    Systems or Databases.
  • Alternatively the Software for handling
    Application Server operations could be a
    custom program or a CGI Script.
  • CGI Script is a compact program
    using Common Gateway Interface
    specification for processing data on a Web
    Server.

26
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATABASES AND THE WEB
  • There are a number of Advantages of using the Web
    to access an Organizations
  • internal Databases
  • 1. Web Browser Software is much more easier to
    use by the users than proprietary Query Tools
    like SQL.
  • 2. The Web Interface requires few or no changes
    to the internal Databases.
  • 3. It also cost much less to add a Web
    interface in front of a Legacy System than to
    redesign and rebuild the Legacy System to improve
    User access.
  • 4. Accessing Corporate Database through the Web
    is creating new efficiencies, opportunities and
    Business Models.

27
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • MANAGING DATA RESOURCES
  • Managing Data Resources after setting up of the
    Database is also important.
  • Special Policies and Procedures, called
    (Information Policies) will be needed for Data
    Management in order to make sure that the data of
    the business remains accurate, reliable, and
    readily available to those who need it.
  • ESTABLISHING AN INFORMATION POLICY
  • An Information Policy specify the organizations
    rules for, acquiring,
  • standardizing , classifying , storing, sharing,
    and disseminating information.
  • An Information Policy lays out specific
    Procedures and accountabilities,
  • identifying which users and organizational units
    can share information, where
  • information can be distributed, and who is
    responsible for updating and
  • maintaining the information.

28
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ESTABLISHING AN INFORMATION POLICY (Continued)
  • A typical example of an Information policy that
    specify only selected Users of the payroll and
    human resources department that would have the
    right to change and view sensitive employee data,
    such as an employees salary or social security
    number, and that the department is responsible
    for making sure that such employee data are
    accurate.
  • The Information Policy in a small business would
    be established by the owners or Managers.
  • In a large organization, managing and planning
    for information as a corporate resource often
    require a formal
  • Data Administration function.

29
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ESTABLISHING AN INFORMATION) POLICY
    (Continued)
  • Data Administration is responsible for the
    specific policies and procedures through which
    data can be managed as an organizational
    resource.
  • Data Administrations responsibilities include
  • Developing information policy,
  • Planning for data,
  • Overseeing Logical Database Design
  • Developing Data Dictionary
  • Monitoring Systems specialists and end-user
    groups usage of data.

30
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ESTABLISHING AN INFORMATION POLICY
    (Continued)
  • Data Governance (promoted by IBM) used to
    describe many of the Information Policy
    activities.
  • Data Governance deals with the Information
    policies and processes for managing the
    availability, usability, integrity, and security
    of the data employed in an enterprise, with
    special emphasis on promoting privacy, security,
    data quality, and compliance with government
    regulations.
  • A Large organization will also have a Database
    Design and Management Group within Information
    Systems Division.
  • Database Design and Management Group is
    responsible for defining and organizing the
    structure and content of the Database, and
    maintaining the Database.
  • The Establishment of the Physical Database, the
    Logical relationships among elements, and the
    access rules and security procedures are
    performed by Database Administration .

31
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • ENSURING DATA QUALITY
  • A well designed Database backed up with an
    Information Policy will go a long
  • way toward ensuring that the business has the
    information it needs.
  • Additional steps must also be taken to ensure
    that the data in Organizational
  • Databases ( Corporate Databases) are accurate
    and remain reliable.
  • If a Database is properly designed and
    Enterprise-wide Data standards established,
    duplicate or inconsistent data elements should be
    minimal.
  • Most Data quality problems, such as misspelled
    names, transposed numbers
  • or incorrect or missing codes, stem from
    errors during data input process.
  • As companies move their businesses to the Web
    and allow customers and
  • Suppliers to enter date that update their
    internal Systems directly via Web,
  • the quality problem caused by the Data
    entry will remain in the agenda.
  • Before a new Database is installed ,
    organizations need to identify and
  • correct their faulty data and establish
    better routines for editing data once their
    Database is in operation.

32
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA QUALITY AUDIT
  • Analysis of Data Quality often begins with a Data
    Quality Audit, which is a
  • structured survey of the accuracy and level of
    completeness of the data in an
  • Information Systems.
  • Data Quality Audits can be performed by
    surveying
  • Entire Data files,
  • Samples from Data files,
  • End-users for their perceptions of Data Quality.

33
FOUNDATIONS OF BUSINESS INTELLIGENCE
  • DATA CLEANSING (DATA SCRUBBING)
  • Data Cleansing is consisted of activities for
    detecting and correcting data in a
  • Database that are incorrect, incomplete,
    improperly formatted, or redundant.
  • Data Cleansing not only corrects errors but also
    enforces consistency among different sets of data
    (File) that originated in separate Information
    Systems.
  • Specialized Data Cleansing Software is available
    to automatically survey data files, correct data,
    and integrate the data in a consistent enterprise
    -wide format.
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