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5. Chapter. Foundations of Business Intelligence: Databases and Information Management. Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management. STUDENT OBJECTIVES.
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5 Chapter Foundations of Business Intelligence: Databases and Information Management
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management STUDENT OBJECTIVES • Describe how a relational database organizes data and compare its approach to an object-oriented 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.
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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.
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. Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 7-Eleven Stores Ask the Customer by Asking the Data
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 7-Eleven Stores Ask the Customer by Asking the Data Interactive Session: 7-Eleven • 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?
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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 5-1
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Normalized Database Design Figure 5-5
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management The Database Approach to Data Management Example Entity-Relationship Diagram Figure 5-6
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management Database Management Systems Capabilities of Database Management Systems • Data definition • Data dictionary • Querying and reporting • Data manipulation language • Structured query language (SQL) • Object-oriented databases
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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 • Subsets of data warehouses that are highly focused and isolated for a specific population of users
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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 5-13
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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 5-14
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making Databases and the Web • 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 • Web interfaces provide familiarity to users and savings over redesigning and rebuilding legacy systems
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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
Essentials of Business Information Systems Chapter 5 Foundations of Business Intelligence: Databases and Information Management 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