Chapter 3: Data and knowledge management. In this chapter, the learning objectives are: Discuss ways that common challenges in managing data can be addressed using data governance, discuss the advantages and disadvantages of relational databases, define big data, and discuss its basic characteristics. | CHAPTER 3 Data and Knowledge Management CHAPTER OUTLINE Managing Data The Database Approach Big Data Data Warehouses and Data Marts Knowledge Management LEARNING OBJECTIVES Discuss ways that common challenges in managing data can be addressed using data governance. Discuss the advantages and disadvantages of relational databases. Define Big Data, and discuss its basic characteristics. Recognize the necessary environment to successfully implement and maintain data warehouses. Describe the benefits and challenges of implementing knowledge management systems in organizations. Managing Data The Difficulties of Managing Data Data Governance The Database Approach Database management system (DBMS) minimizes the following problems: Data redundancy Data isolation Data inconsistency The Database Approach DBMSs maximize the following issues: Data security Data integrity Data independence Data Hierarchy Bit Byte Field Record File (or table) Database The Relational Database Model Database Management System (DBMS) Relational Database Model Data Model Entity Instance Attribute Big Data Defining Big Data Characteristics of Big Data Issues with Big Data Managing Big Data Putting Big Data to Use Data Warehousing Data warehouses and Data Marts Organized by business dimension or subject Multidimensional Historical Use online analytical processing 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. Knowledge Management Knowledge management (KM) Knowledge Explicit Knowledge Tacit Knowledge Intellectual capital (or intellectual assets) Knowledge Management System Cycle Create knowledge Capture knowledge Refine knowledge Store knowledge Manage knowledge Disseminate knowledge Closing Case #1 The Problem The Solution The Results Closing Case #2: The Problem The Solution The Results | CHAPTER 3 Data and Knowledge Management CHAPTER OUTLINE Managing Data The Database Approach Big Data Data Warehouses and Data Marts Knowledge Management LEARNING OBJECTIVES Discuss ways that common challenges in managing data can be addressed using data governance. Discuss the advantages and disadvantages of relational databases. Define Big Data, and discuss its basic characteristics. Recognize the necessary environment to successfully implement and maintain data warehouses. Describe the benefits and challenges of implementing knowledge management systems in organizations. Managing Data The Difficulties of Managing Data Data Governance The Database Approach Database management system (DBMS) minimizes the following problems: Data redundancy Data isolation Data inconsistency The Database Approach DBMSs maximize the following issues: Data security Data integrity Data independence Data Hierarchy Bit Byte Field Record File (or table) Database
