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CS614 Highlighted Handouts Set 2

Data Warehousing PDF 6.2 MBUpdated 23 Oct 2026
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Highlighted handout CS614 Highlighted Handouts Set 2 PDF 6.2 MB
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CS614 Data Warehousing
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23 Oct 2026
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CONTENTS

Lecture 1: Introduction to Data Ware Housing–Part I......................................................... 10

  1. 1 Why Data Warehousing? ....................................................................................10
  2. 2 The Need for a Data Warehouse .........................................................................10
  3. 3 Historical Overview ............................................................................................11
  4. 4 Crisis of Credibility.............................................................................................14

Lecture 2: Introduction to Data Ware Housing – Part II.................................................... 15

  1. 1 Why a Data Warehouse (DWH)?........................................................................15
  2. 2 What is a DWH? .................................................................................................18
  3. 3 Another view of a DWH .....................................................................................19

Lecture 3:

Introduction to Data Ware Housing–Part III .................................................. 21

  1. 1 What is a Data Warehouse? ................................................................................21
  2. 2 How is it different?..............................................................................................22
  3. 3 Why keep historical data? ...................................................................................24
  4. 4 Deviation from the PURIST approach................................................................26

Lecture 4:

Introduction to Data Ware Housing–Part IV .................................................. 28

  1. 1 Typical Queries ...................................................................................................29
  2. 2 Putting the pieces together ..................................................................................31
  3. 3 Why this is hard?.................................................................................................31
  4. 4 High level implementation steps.........................................................................32

Lecture 5:

Introduction to Data Ware Housing–Part V.................................................... 34

  1. 1 Types and Typical Applications of DWH...........................................................34
  2. 2 Telecommunications Data Warehouse................................................................35
  3. 3 Typical Applications of DWH ............................................................................36
  4. 4 Major Issues ........................................................................................................40

Lecture 6: Normalization ........................................................................................................ 41

  1. 1 Normalization......................................................................................................41
  2. 2 Normalization: 1NF ............................................................................................43
  3. 3 Normalization: 2NF ............................................................................................44 Normalization: 3NF .......................................................................................................46
  4. 5 Conclusions.........................................................................................................48

Lecture 07: De-Normalization............................................................................................... 49

  1. 1 What is De-Normalization?.................................................................................49
  2. 2 Why De-Normalization in DSS?.........................................................................50
  3. 3 How De-Normalization improves performance? ................................................50
  4. 4 Four Guidelines for De-normalization................................................................51
  5. 5 Areas for Applying De-Normalization Techniques ............................................52
  6. 6 Five principal De-Normalization techniques ......................................................52

Lecture 08: De-Normalization Techniques .......................................................................... 54

  1. 1 Splitting Tables ...................................................................................................54
  2. 2 Pre-Joining ..........................................................................................................57
  3. 3 Adding Redundant Columns ...............................................................................58
  4. 4 Derived Attributes...............................................................................................60

Lecture 09: Issues of De-Normalization.................................................................................. 62

  1. 1 Storage Issues: Pre-joining..................................................................................62
  2. 2 Performance Issues: Pre-joining..........................................................................63
  3. 3 Other Issues: Adding redundant columns ...........................................................65

Lecture 10: Online Analytical Processing (OLAP) ............................................................. 69

  1. 1 DWH & OLAP................................................................................................69
  2. 2 Analysis of last example..................................................................................71
  3. 3 Challenges .......................................................................................................72
  4. 4 OLAP: Facts & Dimensions............................................................................74
  5. 5 Where Does OLAP Fit In? ..............................................................................74
  6. 6 Difference between OLTP and OLAP.............................................................75
  7. 7 OLAP FASMI Test..........................................................................................76

Lecture 11: Multidimensional OLAP (MOLAP)................................................................. 78

  1. 1 OLAP Implementations...................................................................................78
  2. 2 MOLAP Implementations ...............................................................................78
  3. 3 Cube Operations ..............................................................................................80
  4. 4 MOLAP Evaluation.........................................................................................83
  5. 5 MOLAP Implementation Issues......................................................................84
  6. 6 Partitioned Cubes.............................................................................................84
  7. 7 Virtual Cubes...................................................................................................86

Lecture 12: Relational OLAP (ROLAP) .............................................................................. 87

  1. 1 Why ROLAP?..................................................................................................87
  2. 2 ROLAP as a “Cube”........................................................................................87
  3. 3 ROLAP and Space Requirement.....................................................................90
  4. 4 ROLAP Issues .................................................................................................92
  5. 5 How to reduce summary tables?......................................................................94
  6. 6 Performance vs. Space Trade-off ....................................................................95
  7. 7 HOLAP............................................................................................................96
  8. 9 DOLAP............................................................................................................97

Lecture 13: Dimensional Modeling (DM)............................................................................. 98

  1. 1 The need for ER modeling?.............................................................................98
  2. 2 Why ER Modeling has been so successful?....................................................99
  3. 3 Need for DM: Un-answered Qs.......................................................................99
  4. 4 Need for DM: The Paradox ...........................................................................101
  5. 5 How to simplify an ER data model?..............................................................103
  6. 6 What is DM?..................................................................................................103
  7. 7 Schemas.........................................................................................................104
  8. 8 Quantifying space requirement......................................................................107

Lecture 14: Process of Dimensional Modeling.................................................................... 109

  1. 1 The Process of Dimensional Modeling .........................................................109
  2. 2 Step-1: Choose the Business Process ............................................................109
  3. 3 Step-2: Choosing the Grain ...........................................................................111
  4. 4 The case FOR data aggregation.....................................................................112
  5. 5 The case AGAINST data aggregation...........................................................112
  6. 6 Step 3: Choose Facts......................................................................................115
  7. 7 Step 4: Choose Dimensions...........................................................................115

Lecture 15: Issues of Dimensional Modeling....................................................................... 119

  1. 1 Step-3: Classification of Aggregation Functions...........................................119
  2. 2 Step-3: A Fact-less Fact Table.......................................................................121
  3. 3 Step-4: Handling Multi-valued Dimensions?................................................121
  4. 4 Step-4: DWH Dilemma: Slowly Changing Dimensions...............................123
  5. 5 Creating a Current Value Field......................................................................126
  6. 6 Step-4: Pros and Cons of Handling ...............................................................126

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