• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Lecture 3 Notes

Lecture 3 Notes






Total Views
Views on SlideShare
Embed Views



0 Embeds 0

No embeds



Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
Post Comment
Edit your comment

    Lecture 3 Notes Lecture 3 Notes Presentation Transcript

      • Chapter 3
      • Databases and
      • Data Warehouses
      • Building Business Intelligence
    • Presentation Overview
      • Business Intelligence
      • The Relational Database Model
      • Database Management System Tools
      • Data Warehouses and Data Mining
      • Managing The Information Resource In An Organization
    • Opening Case Study High Tech Battles High School Truancy
      • Organizations need databases (and data warehouses) for organizing and managing information.
      • Why are the implementation of security and privacy measures difficult?
    • Introduction
      • Databases and data warehouses are methods for organizing and managing information and business intelligence.
      • Database management systems and data mining tools are IT tools you use to work with information and business intelligence.
      • Business intelligence - is knowledge about your:
        • Customers
        • Competitors
        • Partners
        • Competitive environment
        • Internal operations
      Business Intelligence
    • Business Intelligence
    • Business Intelligence
      • Two types of information processing include:
        • Online transaction processing ( OLTP ) - the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information.
          • Operational databases - databases that support OLTP.
        • Online analytical processing ( OLAP ) - the manipulation of information to support decision making.
    • Business Intelligence
      • A data warehouse is a special form of a database that contains information gathered from many operational databases for the purpose of supporting decision-making tasks.
    • The Relational Database Model
      • Database - a collection of information that you organize and access according to the logical structure of that information.
      • Relational database model - uses a series of logically related two-dimensional tables or files to store information in the form of a database.
      • Relation - describes each two-dimensional table or file in the relational model.
    • The Relational Database Model
      • Relational databases are composed of two parts:
        • Information – stored in a series of two-dimensional tables, files, or relations.
        • Logical structure of the information.
    • The Relational Database Model Collections of Information
    • The Relational Database Model Created with Logical Structures
      • When you create a database, you first create the data dictionary.
      • Data dictionary - contains the logical structure for the information.
    • The Relational Database Model Created with Logical Structures Part Number is the primary key because of the key icon beside it. For Percentage Markup , we defined its Format as “Percent” and its number of decimal places as 2.
    • The Relational Database Model With Logical Ties Among the Information
      • Primary key - a field (or group of fields in some cases) that uniquely describes each record.
      • Foreign key - a primary key of one file that appears in another file.
    • The Relational Database Model With Logical Ties Among the Information
    • The Relational Database Model With Built-In Integrity Constraints
      • Integrity constraints – rules that help ensure the quality of the information.
      Team Work Primary Keys, Foreign Keys, and Integrity Constraints (p. 133)
    • Database Management System Tools
      • Database management system ( DBMS ) – helps you specify the logical organization for a database and access and use the information within a database.
      • A DBMS contains the following five important software components:
        • DBMS engine
        • Data definition subsystem
        • Data manipulation subsystem
        • Application generation subsystem
        • Data administration subsystem
    • Database Management System Tools
      • DBMS engine - accepts logical requests from the various other DBMS subsystems, converts them into their physical equivalent, and actually accesses the database and data dictionary as they exist on a storage device.
      • Physical view - deals with how information is physically arranged, stored, and accessed on some type of storage device such as a hard disk.
      • Logical view - focuses on how you arrange and access information to meet your particular business needs.
      Database Management System Tools
    • DBMS Tools Data Definition Subsystem
      • Data definition subsystem - helps you create and maintain the data dictionary and define the structure of the files in a database.
      • (For a great overview on the logical properties of information review the table on page 136)
    • DBMS Tools Data Manipulation Subsystem
      • Data manipulation subsystem - helps you add, change, and delete information in a database and mine it for valuable information. Tools here include views, report generators, QBE, and SQL.
      • View - allows you to see the contents of a database file, make whatever changes you want, perform simple sorting, and query to find the location of specific information.
    • DBMS Tools Data Manipulation Subsystem Click here to enter a new record. Find information using the binoculars.
    • DBMS Tools Data Manipulation Subsystem
      • Report generator - helps you quickly define formats of reports and what information you want to see in a report.
    • DBMS Tools Data Manipulation Subsystem
      • By following a series of simple screens, you can easily create the report below.
    • DBMS Tools Data Manipulation Subsystem
      • Query-by-example ( QBE ) tools - help you graphically design the answer to a question.
    • DBMS Tools Data Manipulation Subsystem The QBE grid Our selection criteria
    • DBMS Tools Data Manipulation Subsystem
      • Structured query language ( SQL ) - a standardized fourth-generation query language found in most DBMSs.
      • The SQL below creates the same report in Figure 3.7 on page 139.
        • SELECT Part.[Part Number], Part.Cost, Employee.[Employee
      • Name], Employee.[Employee Number]
      • FROM Part, Employee
      • WHERE (((Part.Cost)>10));
    • DBMS Tools Application Generation Subsystem
      • Application generation subsystem - contains facilities to help you develop transaction-intensive applications.
        • Data entry screens
        • DBMS-specific programming languages
        • Commonly used programming languages
    • DBMS Tools Data Administration Subsystem
      • Data administration subsystem - a DBMS helps you manage the overall database environment by providing facilities for backup and recovery, security management, query optimization, concurrency control, and change management.
      On Your Own DBMS Support OLTP, OLAP, and Information Management (p. 142)
    • DBMS Tools Data Administration Subsystem
      • Backup and recovery facilities:
        • Periodically back up information contained in a database.
        • Restart or recover a database and its information in case of a failure.
      • Security management facilities - control who has access to what information and what type of access those people have.
    • DBMS Tools Data Administration Subsystem
      • Query optimization facilities - take queries from users and restructure them to minimize response times.
      • Reorganization facilities - continually maintain statistics concerning how the DBMS engine physically accesses information.
      • Concurrency control facilities - ensure the validity of database updates when multiple users attempt to access and change the same information.
    • Data Warehouses and Data Mining What Is a Data Warehouse?
      • Data warehouse - a logical collection of information – gathered from many different operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks.
    • Data Warehouses and Data Mining What Is a Data Warehouse?
    • Data Warehouses and Data Mining What Is a Data Warehouse?
      • Data warehouses are not transaction-oriented.
      • Data warehouses support online analytical processing (OLAP).
    • Data Warehouses and Data Mining What Are Data Mining Tools?
      • Data mining tools - software tools you use to query information in a data warehouse. These tools include:
        • Query-and-reporting tools - similar to QBE tools, SQL, and report generators in the typical database environment.
        • Intelligent agents – use various artificial intelligence tools to form the basis of information discovery and building business intelligence in OLAP.
    • Data Warehouses and Data Mining What Are Data Mining Tools?
      • Data mining tools continued
        • Multidimensional analysis ( MDA ) tools - slice-and-dice techniques that allow you to view multidimensional information from different perspectives.
        • Statistical tools – help you apply various mathematical models to the information stored in a data warehouse to discover new information.
    • Data Warehouses and Data Mining What Are Data Mining Tools?
    • Data Warehouses and Data Mining Data Marts – Smaller Data Warehouses
      • Data mart - a subset of a data warehouse in which only a focused portion of the data warehouse information is kept.
    • Data Warehouses and Data Mining Important Considerations
      • Do you need a data warehouse?
      • Do all your employees need an entire data warehouse?
      • How up-to-date must the information be?
      • What data mining tools do you need?
      Team Work How Up-to-Date Should Data Warehouse Information Be? (p. 149)
    • MANAGING THE INFORMATION RESOURCE Who Should Oversee the Organization’s Information?
      • Chief information officer ( CIO ) - responsible for overseeing an organization’s information resource.
      • Data administration - plans for, oversees the development of, and monitors the information resource.
      • Database administration - responsible for the more technical and operational aspects of managing the information contained in organizational databases.
    • MANAGING THE INFORMATION RESOURCE How Will Changes in Technology Affect Organizing and Managing Information?
      • As new technologies become available, you should ask yourself whether those technologies will help you organize and manage your information better.
      • One of the greatest technological changes that will occur over the coming years is a convergence of different tools that will help you better organize and manage information.
    • MANAGING THE INFORMATION RESOURCE Is Information Ownership a Consideration?
      • Information ownership is a key consideration in today’s information-based business environment.
      • Ownership refers to who is responsible for information quality.
      On Your Own CRUD – Defining Information Ownership (p. 151)
    • MANAGING THE INFORMATION RESOURCE What Are the Ethics Involved in Managing and Organizing Information?
      • Databases, data warehouses, DBMSs, and data mining tools make it possible for people to easily access all kinds of organizational information.
      • How does an organization safeguard against the unethical use of information within the organization?
    • Closing Case Study One We’ve Got OLTP Covered; Let’s Go on to OLAP
      • What is the single most important factor that hinders all organizations in general from providing good online analytical processing (OLAP) support?
      • Why is it so much easier for organizations to provide good online transaction processing (OLTP) support?
    • Closing Case Study Two Mining Dining Data
      • Consider the issue of timely information with respect to the businesses discussed in the case.
      • Which of the businesses must have the most up-to-date information in its data warehouse?
    • Summary Student Learning Outcomes
      • Describe business intelligence and its role in an organization.
      • Differentiate between databases and data warehouses with respect to their focus on online transaction processing and online analytical processing.
      • List and describe the key characteristics of a relational database.
      • Define the five software components of a database management system.
    • Summary Student Learning Outcomes
      • List and describe the key characteristics of a data warehouse.
      • Define the four major types of data mining tools in a data warehouse environment.
      • List key considerations in managing the information resource in an organization.
    • Summary Assignments & Exercises
      • Finding “hacked” databases
      • Defining queries for a video rental store
      • Creating a query
      • Career opportunities in your major
      • Salaries for database administrators
    • Visit the Web to Learn More www.mhhe.com/haag
      • Financial aid resources
      • Libraries
      • Consumer information
      • Demographics
      • Real estate
      • Data warehouses and data mining tools