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DWH-Ahsan AbdullahDWH-Ahsan Abdullah
11
Data WarehousingData Warehousing
Lecture-3Lecture-3
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
DWH-Ahsan Abdullah
2
Introduction and BackgroundIntroduction and Background
DWH-Ahsan Abdullah
3
What is a Data Warehouse ?What is a Data Warehouse ?
It is a blend of many technologies, the basic
concept being:

Take all data from different operational systems.

If necessary, add relevant data from industry.

Transform all data and bring into a uniform format.

Integrate all data as a single entity.
DWH-Ahsan Abdullah
4
What is a Data Warehouse ? (Cont…)What is a Data Warehouse ? (Cont…)
It is a blend of many technologies, the basic
concept being:

Store data in a format supporting easy access for
decision support.

Create performance enhancing indices.

Implement performance enhancement joins.

Run ad-hoc queries with low selectivity.
DWH-Ahsan Abdullah
5
Business user
needs info
User requests
IT people
IT people
create reports
IT people
send reports to
business user
IT people do
system analysis
and design
Business user
may get answers
Answers result
in more questions

?
How is it Different?How is it Different?
 Fundamentally differentFundamentally different
DWH-Ahsan Abdullah
6
How is it Different?How is it Different?
 Different patterns of hardware utilizationDifferent patterns of hardware utilization
100%
0%
Operational DWH
Bus Service vs. TrainBus Service vs. Train
DWH-Ahsan Abdullah
7
How is it Different?How is it Different?
 Combines operational and historical data.Combines operational and historical data.
 Don’t do data entry into a DWH, OLTP or ERP are the
source systems.
 OLTP systems don’t keep history, cant get balance
statement more than a year old.
 DWH keep historical data, even of bygone customers. Why?
 In the context of bank, want to know why the customer left?
 What were the events that led to his/her leaving? Why?
 Customer retention.
DWH-Ahsan Abdullah
8
How much history?How much history?
 Depends on:Depends on:
 Industry.Industry.
 Cost of storing historical data.Cost of storing historical data.
 Economic value of historical data.Economic value of historical data.
DWH-Ahsan Abdullah
9
How much history?How much history?
 Industries and historyIndustries and history
 TelecommTelecomm calls are much much more as compared tocalls are much much more as compared to
bank transactions-bank transactions- 18 months18 months..
 RetailersRetailers interested in analyzing yearly seasonalinterested in analyzing yearly seasonal
patterns-patterns- 65 weeks65 weeks..
 InsuranceInsurance companies want to do actuary analysis, usecompanies want to do actuary analysis, use
the historical data in order to predict risk-the historical data in order to predict risk- 7 years7 years..
DWH-Ahsan Abdullah
10
How much history?How much history?
EconomicEconomic valuevalue of dataof data
Vs.Vs.
StorageStorage costcost
Data Warehouse aData Warehouse a
complete repositorycomplete repository of data?of data?
DWH-Ahsan Abdullah
11
How is it Different?How is it Different?
 Usually (but not always) periodic or batchUsually (but not always) periodic or batch
updates rather than real-time.updates rather than real-time.
 The boundary is blurring for active data warehousing.
 For an ATM, if update not in real-time, then lot of real
trouble.
 DWH is for strategic decision making based on historical
data. Wont hurt if transactions of last one hour/day are
absent.
DWH-Ahsan Abdullah
12
How is it Different?How is it Different?
 Rate of update depends on:
 volume of data,
 nature of business,
 cost of keeping historical data,
 benefit of keeping historical data.

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Data Warehousing Introduction and Background

  • 1. DWH-Ahsan AbdullahDWH-Ahsan Abdullah 11 Data WarehousingData Warehousing Lecture-3Lecture-3 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
  • 2. DWH-Ahsan Abdullah 2 Introduction and BackgroundIntroduction and Background
  • 3. DWH-Ahsan Abdullah 3 What is a Data Warehouse ?What is a Data Warehouse ? It is a blend of many technologies, the basic concept being:  Take all data from different operational systems.  If necessary, add relevant data from industry.  Transform all data and bring into a uniform format.  Integrate all data as a single entity.
  • 4. DWH-Ahsan Abdullah 4 What is a Data Warehouse ? (Cont…)What is a Data Warehouse ? (Cont…) It is a blend of many technologies, the basic concept being:  Store data in a format supporting easy access for decision support.  Create performance enhancing indices.  Implement performance enhancement joins.  Run ad-hoc queries with low selectivity.
  • 5. DWH-Ahsan Abdullah 5 Business user needs info User requests IT people IT people create reports IT people send reports to business user IT people do system analysis and design Business user may get answers Answers result in more questions  ? How is it Different?How is it Different?  Fundamentally differentFundamentally different
  • 6. DWH-Ahsan Abdullah 6 How is it Different?How is it Different?  Different patterns of hardware utilizationDifferent patterns of hardware utilization 100% 0% Operational DWH Bus Service vs. TrainBus Service vs. Train
  • 7. DWH-Ahsan Abdullah 7 How is it Different?How is it Different?  Combines operational and historical data.Combines operational and historical data.  Don’t do data entry into a DWH, OLTP or ERP are the source systems.  OLTP systems don’t keep history, cant get balance statement more than a year old.  DWH keep historical data, even of bygone customers. Why?  In the context of bank, want to know why the customer left?  What were the events that led to his/her leaving? Why?  Customer retention.
  • 8. DWH-Ahsan Abdullah 8 How much history?How much history?  Depends on:Depends on:  Industry.Industry.  Cost of storing historical data.Cost of storing historical data.  Economic value of historical data.Economic value of historical data.
  • 9. DWH-Ahsan Abdullah 9 How much history?How much history?  Industries and historyIndustries and history  TelecommTelecomm calls are much much more as compared tocalls are much much more as compared to bank transactions-bank transactions- 18 months18 months..  RetailersRetailers interested in analyzing yearly seasonalinterested in analyzing yearly seasonal patterns-patterns- 65 weeks65 weeks..  InsuranceInsurance companies want to do actuary analysis, usecompanies want to do actuary analysis, use the historical data in order to predict risk-the historical data in order to predict risk- 7 years7 years..
  • 10. DWH-Ahsan Abdullah 10 How much history?How much history? EconomicEconomic valuevalue of dataof data Vs.Vs. StorageStorage costcost Data Warehouse aData Warehouse a complete repositorycomplete repository of data?of data?
  • 11. DWH-Ahsan Abdullah 11 How is it Different?How is it Different?  Usually (but not always) periodic or batchUsually (but not always) periodic or batch updates rather than real-time.updates rather than real-time.  The boundary is blurring for active data warehousing.  For an ATM, if update not in real-time, then lot of real trouble.  DWH is for strategic decision making based on historical data. Wont hurt if transactions of last one hour/day are absent.
  • 12. DWH-Ahsan Abdullah 12 How is it Different?How is it Different?  Rate of update depends on:  volume of data,  nature of business,  cost of keeping historical data,  benefit of keeping historical data.

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