This document provides an introduction and overview of a course on data warehousing. It lists reference books and additional materials for the course. It then summarizes the course topics, which include introduction and background, de-normalization, OLAP, dimensional modeling, ETL, data quality management, performance techniques, data mining, implementation steps, a case study, lab usage, and others. It also describes a semester project where students will develop a data warehouse application for an organization and outlines what should be included in the project report.

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Data WarehousingData Warehousing
Lecture-1Lecture-1
Introduction and BackgroundIntroduction and Background
Virtual University of PakistanVirtual University of Pakistan
Ahsan Abdullah
Assoc. Prof. & Head
Center for Agro-Informatics Research
www.nu.edu.pk/cairindex.asp
FAST National University of Computers & Emerging Sciences, IslamabadFAST National University of Computers & Emerging Sciences, Islamabad

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Introduction and BackgroundIntroduction and Background

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Reference BooksReference Books
 W. H. Inmon,W. H. Inmon, Building the Data WarehouseBuilding the Data Warehouse
(Second Edition),(Second Edition), John Wiley & Sons Inc., NY.John Wiley & Sons Inc., NY.
 A. Abdullah, “A. Abdullah, “Data Warehousing for beginners:Data Warehousing for beginners:
Concepts & IssuesConcepts & Issues”” (First Edition).(First Edition).
 Paulraj Ponniah,Paulraj Ponniah, Data WarehousingData Warehousing
FundamentalsFundamentals,,
John Wiley & Sons Inc., NY.John Wiley & Sons Inc., NY.

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Additional MaterialAdditional Material
 Research PapersResearch Papers
 Magazine ArticlesMagazine Articles

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Summary of courseSummary 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

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

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Summary of courseSummary 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

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

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

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

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

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

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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
1960
Master Files & Reports
1965
Lots of Master files!
1970
Direct Access Memory & DBMS
1975
Online 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 CredibilityHistorical overview: Crisis of Credibility




 
What is the financial health of our company?What is the financial health of our company?
-10%
+10%

??