Foundations of Business Intelligence: Databases and Information Management

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1 Chapter 5 Foundations of Business Intelligence: Databases and Information Management 5.1

2 See Markers-ORDER-DB Logically Related Tables Relational Approach: Physically Related Tables: The Relationship Screen Multi-Table Queries 5.2 Ayati s notes

3 A parallel: Information System: Storage Concept vs. Program Concept: Any Production System Parts Storage Assembly Line Product Any Information System Organized Parts (The value is in the organization) Data Database Program (Instruction Codes) Information 5.3 Ayati s notes Organized Data (a report, a form, on a screen or on paper)

4 Format of Stored Data Text-based ( Free Format ) information: Some 85 % of total written information Record-based ( Formatted ) Information: Some 15 % of total written Information Volume of Data vs. vs. Accessing Data 5.4 Ayati s notes

5 Definition of Database A Broad Definition: Storage of Data and Knowledge in any Medium and any Format A Narrow definition: Storage of Physically Related Data (and Knowledge) in Electronic Medium in either record or text Formats: A Narrower definition, Relevant to This course: Storage of Formatted record based Data (and Knowledge) in Electronic Medium which are Physically Related 5.5 Ayati s notes

6 Database vs. Database Management System (DBMS)? Data Database Program (Instruction Codes) Information (a report, a screen) Data Entry Forms Data Definition Language Data Manipulatio n Language Database Management Systems (DBMS) Reports & Forms Generating Facilities 5.6 Ayati s notes

7 Learning Database Involves: Database Design : How to Design Storage Database Processing: Learning the structure and mechanics of a DBMS 5.7 Ayati s notes

8 Approaches to learning Database: Concept first: The Academic approach Practice first: the Layman approach : The Professional Approach Concept Practice 5.8 Ayati s notes

9 STUDENT OBJECTIVES Describe how a relational database organizes data and compare its approach to an objectoriented database. Identify and describe the principles of a database management system. Evaluate tools and technologies for providing information from databases to improve business performance and decision making. 5.9

10 STUDENT OBJECTIVES (Continued) Assess the role of information policy and data administration in the management of organizational data resources. Assess the importance of data quality assurance for the business. 5.10

11 7-Eleven Stores Ask the Customer by Asking the Data Problem: Detached view of customer base, inadequate sales data. Solutions: Implement retail information system and database and deploy POS workstations to analyze customer preferences and analyze sales trends. HP servers and Retail Information System leads to reduced inventory and increased sales revenue. Demonstrates IT s role in establishing customer intimacy and managing inventory. Illustrates digital technology s role in forging success in business from data harvesting. 5.11

12 7-Eleven Stores Ask the Customer by Asking the Data Interactive Session: 7-Eleven7 What are your experiences with shopping at your local convenience store? Does the store ever run out of your favorite items? If so, how quickly are they replaced? Does the store proprietor have a relationship with his or her customers? Are you aware of purchase data being collected? Are you more or less likely to shop at a convenience store when you know that your purchase data are being collected? Are you more or less likely to frequent a store that caters to your personal buying habits? 5.12

13 The Database Approach to Data Management Database: a collection of related files containing records on people, places, or things Entities and attributes Organizing data in a relational database Fields, records, key fields, primary key, foreign key Establishing relationships Entity-relationship diagram, normalization, join table 5.13

14 The Database Approach to Data Management A Relational Database Table A relational database organizes data in the form of two-dimensional tables. Illustrated here is a table for the entity SUPPLIER showing how it represents the entity and its attributes. Supplier_Number is the key field. Figure

15 The Database Approach to Data Management A Simple Entity-Relationship Diagram This diagram shows the relationship between the entities SUPPLIER and PART. Figure

16 Database Management Systems DBMS A specific type of software for creating, storing, organizing, and accessing data from a database Separates the logical and physical views of the data Logical view: how end users view data Physical view: how data are actually structured and organized Examples of DBMS: Microsoft Access, DB2, Oracle Database, Microsoft SQL Server, MYSQL 5.16

17 Database Management Systems Operations of a Relational DBMS Select: creates a subset of records based on stated criteria Join: combines relational tables to present the user with more information than is available from individual tables Project: creates a subset consisting of columns in a table 5.17

18 Capabilities of Database Management Systems Data definition Data dictionary Essentials of Business Information Systems Querying and reporting Data manipulation language Structured query language (SQL) Object-oriented databases Database Management Systems 5.18

19 Using Databases to Improve Business Performance and Decision Making Data Warehouses What is a data warehouse? A database that stores current and historical data that may be of interest to decision makers Data marts Essentials of Business Information Systems Subsets of data warehouses that are highly focused and isolated for a specific population of users 5.19

20 Using Databases to Improve Business Performance and Decision Making Components of a Data Warehouse The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined with data from external sources and reorganized into a central database designed for management reporting and analysis. The information directory provides users with information about the data available in the warehouse. Figure

21 Using Databases to Improve Business Performance and Decision Making Business Intelligence, Multidimensional Data Analysis, and Data Mining Business intelligence: tools for consolidating, analyzing, and providing access to large amounts of data to improve decision making Online analytical processing (OLAP) Data mining and predictive analysis Associations Sequences Classifications Clusters Forecasts 5.21

22 Using Databases to Improve Business Performance and Decision Making Business Intelligence A series of analytical tools works with data stored in databases to find patterns and insights for helping managers and employees make better decisions to improve organizational performance. Figure

23 Using Databases to Improve Business Performance and Decision Making Peru s Banco de Credito Scores with a New Data Warehouse Read the Focus on Organizations and then discuss the following questions: What problems does Banco de Credito Peru face? How do the problems affect the bank s strategy and business performance? How did management choose to solve these problems? Analyze the people, organization, and technology dimensions of its solution. What alternatives were available to management? Did management choose the best alternative? Explain your answer. 5.23

24 Using Databases to Improve Business Performance and Decision Making Firms use the Web to make information from their internal databases available to customers and partners Middleware and other software make this possible Database servers CGI Databases and the Web Web interfaces provide familiarity to users and savings over redesigning and rebuilding legacy systems 5.24

25 Managing Data Resources Establishing an Information Policy An information policy states an organization s rules for managing and storing information Data administration is responsible for the specific policies and procedures through which data can be managed as a resource Large organizations use a database design and management group to perform database administration 5.25

26 Managing Data Resources Ensuring Data Quality Poor data quality is a major obstacle to successful customer relationship management Data quality problems can be caused by redundant and inconsistent data produced by multiple systems Data input errors are the cause of many data quality problems A data quality audit is a structured survey of the accuracy and completeness of data Data cleansing detects and corrects incorrect, incomplete, improperly formatted, and redundant data 5.26

27 Managing Data Resources Downloading Digital Music When You re on the Wrong Track Read the Focus on Technology and then discuss the following questions: What data management and data quality problems are posed by digital music services? What is the impact of these problems on individuals and the digital music industry? What people, organization, and technology factors were involved? What alternative solutions are available? 5.27

28 Managing Data Resources Interactive Session: Downloading Digital Music What experiences have you had with bad data in relation to digital music? Visit the Gracenote Web site at and search the music database for a few of your favorite songs and artists. Are you able to find any bad or conflicting data? How concerned are you with having correct metadata for your digital music? What steps do you take to protect the quality of your metadata? 5.28

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