Transcript chapter07
7-1 Chapter 7 Secondary Data Searches 7-2 Learning Objectives Understand the . . . • purpose and process of exploratory research • two types and three levels of management decision-related secondary sources • five types of external information and the factors for evaluating the value of a source and its content 7-3 Learning Objectives Understand . . . • the process for conducting a literature search • data mining and how internal data mining techniques differ from literature searches. 7-4 Exploratory Phase Search Strategy Discovery/ Analysis Secondary Sources Expert Interview Search Strategy Individual Depth Interviews Group Discussions 7-5 Exhibit 7-1 Integration of Secondary Data into the Research Process 7-6 Objectives of Secondary Searches • Expand understanding of management dilemma • Gather background information • Identify information that should be gathered • Identify sources for and actual questions that might be used • Identify sources for and actual sample frames that might be used 7-7 Conducting a Literature Search Define management dilemma Consult books for relevant terms Use terms to search Locate/review secondary sources Evaluate value of each source and content 7-8 • Whiteboard technology makes the discussion of symptoms relevant to the managementresearch question hierarchy easier 7-9 Levels of Information Primary Sources: Memos Letters Interviews Speeches Laws Internal records Secondary Sources: Encyclopedias Textbooks Handbooks Magazines Newspapers Newscasts Tertiary Sources: Indexes Bibliographies Internet search engines 7-10 Exhibit 7-2 Integrating Secondary Data 7-11 The U.S. Government is the world’s largest source of data 7-12 Information Sources Indexes/ Bibliographies Directories Dictionaries Types Handbooks Encyclopedias 7-13 Evaluating Information Sources Purpose Format Scope Evaluation Factors Audience Authority 7-14 Exhibit 7-4 Review of Advanced Search Options 7-15 Exhibit 7-5 Advanced Searching Process 7-16 Exhibit 7-9 The Evolution of Data Mining Evolutionary Step Investigative Question Enabling Technologies Characteristics Data collection (1960s) “What was my average total revenue over the last five years?” Computers, tapes, disks Retrospective, static data delivery Data access (1980s) “What were unit sales in California last December?” Relational databases (RDBMS), structured query language (SQL), ODBC Retrospective, dynamic data delivery at record level Data navigation (1990s) “What were unit sales in California last December? Drill down to Sacramento.” Online analytic processing (OLAP), multidimensional databases, data warehouses Retrospective, dynamic data delivery at multiple levels Data mining (2000) “What’s likely to happen to Sacramento unit sales next month? Why?” Advanced algorithms, multiprocessor computers, massive databases Prospective, proactive information delivery 7-17 Exhibit 7-10 Data Mining in Business 7-18 Exhibit 7-12 Data-Mining Process 7-19 Key Terms • • • • • • • • • • • • Bibliography Bibliographic Database Data Mart Data Mining Data Visualization Data Warehouse Dictionary Directory Encyclopedia Exploratory research Handbook Individual depth interview • • • • • • • Index Literature search Portal Primary sources Search query Secondary sources Source evaluation – – – – – Purpose Scope Authority Audience Format • Tertiary sources