Lecture 9 : Business Intelligence and Information Systems for Decision Making

Transcription

1 MANAGEMENT INFORMATION SYSTEMS Lecture 9 : Business Intelligence and Information Systems for Decision Making 1

2 Class Website 2

3 Course Textbooks - Recommended 3

4 Session Objectives It is expected that at the end of the session, students will understand: Why organizations need business intelligence. How business intelligence (BI) systems provide competitive advantages. The Three primary activities in the BI process. Problems operational data pose for BI systems. The purpose and components of a data warehouse Differences between data mart and data warehouse. The characteristics of data mining systems. 4

5 Business Intelligence Business intelligence (BI) Refers to information containing, patterns, relationships, and trends. For instance, statistics from 10 years records of Ghana Cedis stability, shows evidence of depreciating Cedi during election years. 5

6 Business Intelligence Systems Businesses use business intelligence systems to process immense ocean of data; to produce patterns, relationships, and other forms of information; and to deliver that information on a timely basis to users who need it. Business intelligence (BI) system is an information system that provides information for improving decision making. 6

7 Three Primary Activities in the BI Process Acquire Data Perform Analysis Publish Results 7

8 Categories of business intelligence Reporting Systems Data mining Systems Knowledge Management Systems Expert Systems systems 8

9 Reporting Systems Reporting systems integrate data from multiple sources, and then process that data by sorting, grouping, summing, averaging, and comparing. They also format the results into reports and deliver them to the right users. Reporting systems improve decision making by providing the right information to the right user at the right time. 9

10 Data mining Systems Data mining systems process data using sophisticated statistical techniques, such as regression analysis and decision tree analysis to find patterns and relationships that cannot be found by simpler reporting operations, such as sorting, grouping, and averaging. Data mining systems improve decision making by using the discovered patterns and relationships to anticipate events or to predict future outcomes. 10

11 Knowledge Management Systems Knowledge management (KM) systems create value from intellectual capital by collecting and sharing human knowledge of products, product uses, best practices, and other critical knowledge with employees, managers, customers, suppliers, and others who need it. 11

12 Expert Systems Expert systems encapsulate the knowledge of human experts in the form of If/Then rules. In a medical diagnosis system, for example, an expert system might have a rule such as: If Patient_Temperature > 103, Then Initiate High_Fever Procedure Operational expert systems can have hundreds or even thousands of such rules. 12

13 Possible Problems with Source Data 13

14 Data Mart vrs Data Warehouse A data mart is a data collection that is created to address the needs of a particular business function, problem, or opportunity. A data mart is a subset of a data warehouse that addresses a particular component or functional area of the business. 14

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16 Data Warehouse The data warehouse takes data from the data manufacturers (operational systems, other internal systems) cleans and processes the data, and locates the data on disks of the data warehouse computers. Data warehouses are bigger than marts and are manned by data management experts. 16

17 Functions of a Data Warehouse Obtain or extract data from operational, internal and external databases Cleanse data Organize, relate, store in a data warehouse database DBMS interface between data warehouse database and BI applications Maintain metadata catalog 17

18 Components of a Data Warehouses 18

19 References David M. Kroenke (2012) Experiencing MIS. 3 rd Edition, Prentice Hall. David M. Kroenke (2010) MIS Essentials. 2 nd Edition, Prentice Hall. Kenneth C. Laudon and Jane P. Laudon (2009). Essentials of Management Information Systems. 8th Edition, Pearson Prentice Hall. 19

20 Next Lecture Information Systems Development 20