Data and Knowledge Management

CHAPTER 5

5.1 Managing Data5.2 The Database Approach5.3 Database Management Systems

5.4 Data Warehouses and Data Marts

5.5 Knowledge Management

CHAPTER OUTLINE

1. Identify three common challenges in managing data, and describe one way organizations can address each challenge using data governance.2. Name six problems that can be minimized by using the database approach.3. Demonstrate how to interpret relationships depicted in an entity-relationship diagram.4. Discuss at least one main advantage and one main disadvantage of relational databases.

LEARNING OBJECTIVES

5. Identify the six basic characteristics of data warehouses, and explain the advantages of data warehouses and marts to organizations.6. Demonstrate the use of a multidimensional model to store and analyze data.7. List two main advantages of using knowledge management, and describe the steps in the knowledge management system cycle.

LEARNING OBJECTIVES (CONTINUED)

ANNUAL FLOOD OF DATA FROM…..

Credit card swipes

E-mails

Digital video

Online TV

RFID tags

Blogs

Digital video surveillance

Radiology scans

Source: Media Bakery

ANNUAL FLOOD OF NEW DATA!

In the zettabyte range

A zettabyte is 1000 exabytes

© Fanatic Studio/Age Fotostock America, Inc.

5.1 MANAGING DATA

The Difficulties of Managing Data

Data Governance

DIFFICULTIES IN MANAGING DATA

Source: Media Bakery

DATA GOVERNANCE

See video

•Data Governance

•Master Data Management

•Master Data

MASTER DATA MANAGEMENT

John Stevens registers for Introduction to Management Information Systems (ISMN 3140) from 10 AM until 11 AM on Mondays and Wednesdays in Room 41 Smith Hall, taught by Professor Rainer.

Transaction Data Master DataJohn Stevens StudentIntro to Management Information Systems CourseISMN 3140 Course No.10 AM until 11 AM TimeMondays and Wednesdays WeekdayRoom 41 Smith Hall LocationProfessor Rainer Instructor

Database management system (DBMS) minimize the following problems:

Data redundancyData isolationData inconsistency

5.2 THE DATABASE APPROACH

DBMSs maximize the following issues:

Data securityData integrityData independence

DATABASE APPROACH (CONTINUED)

DATABASE MANAGEMENT SYSTEMS

BitByteFieldRecordFile (or table)Database

DATA HIERARCHY

HIERARCHY OF DATA FOR A COMPUTER-BASED FILE

Bit (binary digit)

Byte (eight bits)

DATA HIERARCHY (CONTINUED)

Example of Field and Record

DATA HIERARCHY (CONTINUED)

Example of Field and Record

DATA HIERARCHY (CONTINUED)

Data modelEntityAttributePrimary keySecondary keys

DESIGNING THE DATABASE

Database designers plan the database design in a process called entity-relationship (ER) modeling.

ER diagrams consists of entities, attributes and relationships.

Entity classes Instance Identifiers

ENTITY-RELATIONSHIP MODELING

RELATIONSHIPS BETWEEN ENTITIES

ENTITY-RELATIONSHIP DIAGRAM MODEL

Database management system (DBMS)

Relational database model Structured Query Language (SQL)

Query by Example (QBE)

5.3 DATABASE MANAGEMENT SYSTEMS

STUDENT DATABASE EXAMPLE

Normalization

Minimum redundancy

Maximum data integrityBest processing performance

Normalized data occurs when attributes in the table depend only on the primary key.

NORMALIZATION

NON-NORMALIZED RELATION

NORMALIZING THE DATABASE (PART A)

NORMALIZING THE DATABASE (PART B)

NORMALIZATION PRODUCES ORDER

Data warehouses and Data Marts Organized by business dimension or subject Multidimensional Historical Use online analytical processing

5.4 DATA WAREHOUSING

DATA WAREHOUSE FRAMEWORK & VIEWS

RELATIONAL DATABASES

MULTIDIMENSIONAL DATABASE

EQUIVALENCE BETWEEN RELATIONAL AND

MULTIDIMENSIONAL DATABASES

EQUIVALENCE BETWEEN RELATIONAL AND

MULTIDIMENSIONAL DATABASES

EQUIVALENCE BETWEEN RELATIONAL AND

MULTIDIMENSIONAL DATABASES

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.

BENEFITS OF DATA WAREHOUSING

Knowledge management (KM) KnowledgeIntellectual capital (or intellectual assets)

5.5 KNOWLEDGE MANAGEMENT

© Peter Eggermann/Age Fotostock America, Inc.

KNOWLEDGE MANAGEMENT (CONTINUED)

Tacit Knowledge(below the waterline)

Explicit Knowledge (above the waterline)

© Ina Penning/Age Fotostock America, Inc.

Knowledge management systems (KMSs)

Best practices

KNOWLEDGE MANAGEMENT (CONTINUED)

© Peter Eggermann/Age Fotostock America, Inc.

Create knowledgeCapture knowledgeRefine knowledgeStore knowledgeManage knowledgeDisseminate knowledge

KNOWLEDGE MANAGEMENT SYSTEM CYCLE

KNOWLEDGE MANAGEMENT SYSTEM CYCLE

CHAPTER CLOSING CASE

• The Problem

• The Solution

• The Results