Data Warehousing Lecture-1

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Introduction and Background

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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.

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Additional Material

– Research Papers

– Magazine Articles

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Summary of courseTopics (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 Abdullah 5

Summary of course

Topics

1. Introduction & Background

2. De-normalization

3. On Line Analytical Processing (OLAP)

4. Dimensional modeling

6

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

Summary of course

Topics

10. Complete implementation case study

11. Lab and tool usage

12. Others

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Semester ProjectDevelop 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.

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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.

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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.

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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.

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The needThe need

Knowledge is power, Intelligence is absolute power!

“Drowning in data and starving for information”

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The needThe need

DATA

INFORMATION

KNOWLEDGE

POWER

INTELLIGENCE

$$

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Historical overviewHistorical overview

1960Master Files & Reports

1965Lots of Master files!

1970Direct Access Memory & DBMS

1975Online high performance transaction processing

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Historical overviewHistorical overview

1980 PCs and 4GL Technology (MIS/DSS)

1985 & 1990 Extract programs, extract processing,

The legacy system’s web

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Historical overview: Crisis of Historical overview: Crisis of CredibilityCredibility

What is the financial health of our company?What is the financial health of our company?

-10%

+10%

??