introduction to information systems
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Introduction to Information Systems. HTM 304 - Management Information Systems College of Business Administration California State University @ San Marcos Authors: Turban, Rainer and Potter Publisher: John Wiley & Sons, Inc. Chapter 4. Data and Knowledge Management. Chapter Outline. - PowerPoint PPT PresentationTRANSCRIPT
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 1
Introduction to Information Systems
HTM 304 - Management Information Systems
College of Business AdministrationCalifornia State University @ San Marcos
Authors: Turban, Rainer and Potter Publisher: John Wiley & Sons, Inc.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 2
Chapter 4
Data and Knowledge Management
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 3
Chapter Outline
4.1 Managing Data 4.2 The Database Approach 4.3 Database Management Systems 4.4 Data Warehousing 4.5 Data Visualization 4.6 Knowledge Management
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 4
Learning Objectives
Recognize the importance of data, issues involved in managing data and their lifecycle.
Describe the sources of data and explain how data are collected.
Explain the advantages of the database approach. Explain the operation of data warehousing and its
role in decision support.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 5
Learning Objectives (Continued)
Understand the capabilities and benefits of data mining.
Describe data visualization. Explain geographic information systems and
virtual reality as decision support tools. Define knowledge and describe the different
types of knowledge.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 6
4.1 Managing Data
Difficulties of Managing Data. Amount of data increases exponentially. Data are scattered and collected by many
individuals using various methods and devices. Data come from many sources including internal
sources, personal sources and external sources. Data security, quality and integrity are critical.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 7
Managing Data (Continued)
Clickstream data. Data that visitors and customers produce when they visit a Website.
An ever-increasing amount of data needs to be considered in making organizational decisions.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 8
Data Life Cycle
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 9
Data Hierarchy
Bit (a binary digit): a circuit that is either on or off.
Byte: group of 8 bits, represents a single character.
Field: name, number, or characters that describe an aspect of a business object or activity.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 10
Data Hierarchy (Continued)
Record: collection of related data fields.
File (or table): collection of related records.
Database: a collection of integrated and related files.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 11
4.2 Database Approach
Database management system (DBMS) provides all users with access to all the data.
DBMSs minimizes the following problems: Data redundancy: the same data stored in many places. Data isolation: applications cannot access data
associated with other applications. Data inconsistency: various copies of the data do not
agree.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 12
Database Approach (Continued)
DBMSs maximize the following issues: Data security. Data integrity: data meets certain constraints, no
alphabetic characters in zip code field. Data independence: applications and data are
independent of one another, all applications are able to access the same data.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 13
Designing the Database
Data model. Diagram that represents the entities in the database and their relationships. Entity is a person, place, thing or event. Attribute is a characteristic or quality of a particular entity. Primary key is a field that uniquely identifies that record. Secondary keys are fields that have identifying information
but may not identify with complete accuracy.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 14
Entity-Relationship Modeling
Database designers plan the database design in a process called entity-relationship (ER) modeling.
ER diagrams consists of entities, attributes and relationships.
Entity classes are a group of entities of a given type, i.e. STUDENT.
Instance is the representation of a particular entity, i.e. STUDENT(John Smith, 123-45-6789, …).
Identifiers are attributes unique to that entity instance, i.e. StudentIDNumber.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 15
4.3 Database Management Systems
Database management system (DBMS) is a set of programs that provide users with tools to add, delete, access and analyze data stored in one location.
Online transaction processing (OLTP) is when transactions are processed as soon as they occur.
Relational database model is based on the concept of two-dimensional tables.
Popular examples of relational databases are Microsoft Access and Oracle.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 16
Query Languages
Structured query language (SQL) is the most popular query language used to request information.
Query by example (QBE) is a grid or template that a user fills out to construct a sample or description of the data wanted.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 17
Relational Database Management Systems
Normalization is a method for analyzing and reducing a relational database to its most streamlined form for: Mimimum redunancy; Maximum data integrity; Best processing performance.
Normalized data is when attributes in the table depend only on the primary key.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 18
Virtual Databases
Software applications that provide a way of managing many different data sources as though they were all one large database.
Benefits of virtual databases include: Lower development costs; Faster development time; Less maintenance; Single point of entry into a company’s data.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 19
4.4 Data Warehousing
Data warehouse is a repository of historical data organized by subject to support decision makers in the organization and include: Online analytical processing which involves
the analysis of accumulated data by end users; Multidimensional data structure which allows
data to be represented in a three-dimensional matrix (or data cube).
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 20
Benefits of Data Warehousing
End users can access data quickly and easily via Web browsers because they are located in one place.
End users can conduct extensive analysis with data in ways that may not have been possible before.
End users have a consolidated view of organizational data.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 21
Data Marts & Data Mining
Data mart is a small data warehouse, designed for the end-user needs in a strategic business unit (SBU) or a department.
Data mining involves searching for valuable business information in a large database, data warehouse, or data mart. Used to predict trends and behaviors. Identify previously unknown patterns.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 22
Data Mining Applications
Retailing and sales. Predict sales, prevent theft and fraud, determine correct inventory levels and distribution schedules.
Banking. Forecast levels of bad loans, fraudulent credit card use, predict credit card spending by new customers, etc.
Manufacturing and production. Predict machinery failures, find key factors to help optimize manufacturing capacity.
Insurance. Forecast claim amounts, medical coverage costs, predict which customers will buy new insurance policies.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 23
Data Mining Applications (Continued)
Policework. Track crime patterns, locations, criminal behavior; identify attributes to assist in solving criminal cases.
Health care. Correlate demographics of patients with critical illnesses, develop better insight to identify and treat symptoms and their causes.
Marketing. Classify customer demographics to predict how customers will respond to mailing or buy a particular product.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 24
4.5 Data Visualization Technologies
Geographic Information Systems (GIS) is a computer-based system for capturing, integrating, manipulating and displaying data using digitized maps. Find locations for new restaurants. Emerging GIS applications integrated with global
positioning systems (GPSs). Virtual Reality is interactive, computer-generated,
three-dimensional graphics delivered to the user through a head-mounted display.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 25
4.6 Knowledge Management
Knowledge management (KM) is a process that helps organizations manipulate important knowledge that is part of the organization’s memory, usually in an unstructured format.
Knowledge is information that is contextual, relevant and actionable; information in action.
Intellectual capital (or intellectual assets) is another term often used for knowledge.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 26
Knowledge Management (Continued)
Explicit knowledge deals with more objective, rational and technical knowledge.
Tacit knowledge is the cumulative store of subjective or experiential learning.
Knowledge management systems (KMSs) use modern information technologies – Internet, intranets, extranets, data warehouses - to systemize, enhance and expedite intrafirm and interfirm knowledge management.
Best practices are the most effective and efficient ways of doing things, readily available to a wide range of employees.
Copyright 2007 John Wiley & Sons, Inc.
Chapter 4 27
Knowledge Management System Cycle
Create knowledge. Determine new ways. Capture knowledge. Identify as valuable. Refine knowledge. Make it actionable. Store knowledge. Store in a reasonable format. Manage knowledge. Verify it is relevant, accurate. Disseminate knowledge. Made available.