1. Data Warehousing Lecture-1 1

2. Introduction and Background 2

3. Reference Books – W. H. Inmon, Building the Data Warehouse (Second Edition), John Wiley & Sons Inc., NY. – A. Abdullah, “Data Warehousing for beginners: Concepts & Issues” (First Edition). – Paulraj Ponniah, Data Warehousing Fundamentals, John Wiley & Sons Inc., NY. 3

4. Additional Material – Research Papers – Magazine Articles 4

5. Summary of course Topics (Total Lectures = 45) 1. Introduction & Background 2. De-normalization 3. On Line Analytical Processing (OLAP) 4. Dimensional modeling 5. Extract – Transform – Load (ETL) 6. Data Quality Management (DQM) 7. Need for speed (Parallelism, Join and Indexing techniques) 8. Data Mining 9. DWH Implementation steps 10. Complete implementation case study 11. Lab and tool usage 12. Others DWH-Ahsan Abdullah5

6. Summary of course Topics 1. Introduction & Background 2. De-normalization 3. On Line Analytical Processing (OLAP) 4. Dimensional modeling 6

7. Summary of course Topics 5. Extract – Transform – Load (ETL) 6. Data Quality Management (DQM) 7. Need for speed (Parallelism, Join and Indexing techniques) 8. Data Mining 9. DWH Implementation steps 7

8. Summary of course Topics 10. Complete implementation case study 11. Lab and tool usage 12. Others 8

9. Semester Project Develop an application for an organization of your choice. A case study and coding based approach to be followed. Use 4GL or a high level programming language. You MUST collect the necessary data and should have a first draft of the project description approved by the instructor BEFORE initiating on detailed work. 9

10. Semester Project (Cont…) The project report to include, but is not limited to, the following as documentation: Narrative description of business and tables of appropriate data. Descriptions of decisions to be supported by information produced by system. Summary narrative of results produced. Structure charts, dataflow diagrams and/or other diagrams to document the structure of the system. Listings of computer models/programs utilized. Reports displaying results. Recommended decision from results. User instructions. 10

11. Approach of the course Develop an understanding of underlying RDBMS concepts. Apply these concepts to VLDB DSS environments and understand where and why they break down? Expose the differences between RDBMS and Data Warehouse in the context of VLDB. Provide the basics of DSS tools such as OLAP, Data Mining and demonstrate their application. Demonstrate the application of DSS concepts and limitations of the OLTP concepts through lab exercises. 11

12. Why this course? The world is changing (actually changed), either change or be left behind. Missing the opportunities or going in the wrong direction has prevented us from growing. What is the right direction? Harnessing the data, in a knowledge driven economy. 12

13. 13 The need Knowledge is power, Intelligence is absolute power! “Drowning in data and starving for information”

14. 14 The need DATA INFORMATION KNOWLEDGE POWER INTELLIGENCE $

15. 15 Historical overview 1960 Master Files & Reports 1965 Lots of Master files! 1970 Direct Access Memory & DBMS 1975 Online high performance transaction processing 

16. 16 Historical overview 1980 PCs and 4GL Technology (MIS/DSS) 1985 & 1990 Extract programs, extract processing, The legacy system’s web  

17. 17 Historical overview: Crisis of Credibility       What is the financial health of our company? -10% +10% ??