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Virtual University of Pakistan. Data Warehousing. Lecture-4 Introduction and Background. Ahsan Abdullah Assoc. Prof. & Head Center for Agro-Informatics Research www.nu.edu.pk/cairindex.asp FAST National University of Computers & Emerging Sciences, Islamabad. Introduction and Background.

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Data warehousing

Virtual University of Pakistan

Data Warehousing

Lecture-4

Introduction and Background

Ahsan Abdullah

Assoc. Prof. & Head

Center for Agro-Informatics Research

www.nu.edu.pk/cairindex.asp

FAST National University of Computers & Emerging Sciences, Islamabad

DWH-Ahsan Abdullah


Introduction and background
Introduction and Background

DWH-Ahsan Abdullah


How is it different
How is it Different?

  • Starts with a 6x12 availability requirement ... but 7x24 usually becomes the goal.

  • Decision makers typically don’t work 24 hrs a day and 7 days a week. An ATM system does.

  • Once decision makers start using the DWH, and start reaping the benefits, they start liking it…

  • Start using the DWH more often, till want it available 100% of the time.

DWH-Ahsan Abdullah


How is it different1
How is it Different?

  • Starts with a 6x12 availability requirement ... but 7x24 usually becomes the goal.

  • For business across the globe, 50% of the world may be sleeping at any one time, but the businesses are up 100% of the time.

  • 100% availability not a trivial task, need to take into account loading strategies, refresh rates etc.

DWH-Ahsan Abdullah


How is it different2

Requirements

Program

How is it Different?

  • Does not follows the traditional development model

  • Classical SDLC

  • Requirements gathering

  • Analysis

  • Design

  • Programming

  • Testing

  • Integration

  • Implementation

DWH-Ahsan Abdullah


How is it different3

DWH

Program

Requirements

How is it Different?

  • Does not follows the traditional development model

  • DWH SDLC (CLDS)

  • Implement warehouse

  • Integrate data

  • Test for biasness

  • Program w.r.t data

  • Design DSS system

  • Analyze results

  • Understand requirement

DWH-Ahsan Abdullah


Data warehouse vs oltp
Data Warehouse Vs. OLTP

OLTP (On Line Transaction Processing)

Select tx_date, balance from tx_table

Where account_ID = 23876;

DWH-Ahsan Abdullah


Data warehouse vs oltp1
Data Warehouse Vs. OLTP

DWH

Select balance, age, sal, gender from customer_table, tx_table

Where age between (30 and 40) and

Education = ‘graduate’ and

CustID.customer_table = Customer_ID.tx_table;

DWH-Ahsan Abdullah


Data warehouse vs oltp2
Data Warehouse Vs. OLTP

DWH-Ahsan Abdullah


Data warehouse vs oltp3
Data Warehouse Vs. OLTP

OLTP: OnLine Transaction Processing (MIS or Database System)

DWH-Ahsan Abdullah


Comparison of response times
Comparison of Response Times

  • On-line analytical processing (OLAP) queries must be executed in a small number of seconds.

    • Often requires denormalizationand/or sampling.

  • Complex query scripts and large list selections can generally be executed in a small number of minutes.

  • Sophisticated clustering algorithms (e.g., data mining) can generally be executed in a small number of hours (even for hundreds of thousands of customers).

DWH-Ahsan Abdullah


Putting the pieces together

www data

OLAP Servers

(Tier 2)

Clients

(Tier 3)

Semistructured

Sources

Query/Reporting

MOLAP

Extract

Transform

Load

(ETL)

Analysis

Business

Users

ROLAP

IT

Users

Data Mining

Operational

Data Bases

Business Users

Archived

data

Data

(Tier 0)

Data Warehouse Server

(Tier 1)

Meta

Data

Data

Warehouse

Data sources

Data Marts

Tools

DWH-Ahsan Abdullah


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