Data Warehousing Lecture-4

Introduction and Background

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Introduction and Background

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How is it Different?• Starts with a 6x12 availability requirement ... but

7x24 usually becomes the goal.

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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.

How is it Different?• Starts with a 6x12 availability requirement ... but

7x24 usually becomes the goal.

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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.

How is it Different?• Does not follows the traditional development

model

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Classical SDLC

Requirements gathering Analysis Design Programming Testing Integration Implementation

Requirements

Program

How is it Different?• Does not follows the traditional development

model

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DWH SDLC (CLDS)

Implement warehouse Integrate data Test for biasness Program w.r.t data Design DSS system Analyze results Understand requirement

Requirements

Program

DWH

Data Warehouse Vs. OLTP

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OLTP (On Line Transaction Processing)OLTP (On Line Transaction Processing)

Select tx_date, balance from tx_tableWhere account_ID = 23876;

Data Warehouse Vs. OLTP

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DWHDWH

Select balance, age, sal, gender from customer_table, tx_tableWhere age between (30 and 40) andEducation = ‘graduate’ andCustID.customer_table = Customer_ID.tx_table;

Data Warehouse Vs. OLTP

OLTP DWH

Primary key used Primary key NOT used

No concept of Primary Index Primary index used

Few rows returned Many rows returned

May use a single table Uses multiple tables

High selectivity of query Low selectivity of query

Indexing on primary key (unique)

Indexing on primary index (non-unique)

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Data Warehouse Vs. OLTP

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Data Warehouse OLTP Scope * Application –Neutral

* Single source of “truth” * Evolves over time * How to improve business

* Application specific * Multiple databases with repetition * Off the shelf application * Runs the business

Data Perspective

* Historical, detailed data * Some summary * Lightly denormalized

* Operational data * No summary * Fully normalized

Queries * Hardly uses PK * Number of results returned in thousands

* Based on PK * Number of results returned in hundreds

Time factor * Minutes to hours * Typical availability 6x12

* Sub seconds to seconds * Typical availability 24x7

OLTP: OnLine Transaction Processing (MIS or Database System)

Comparison of Response Times• On-line analytical processing (OLAP) queries must be

executed in a small number of seconds.– Often requires denormalization and/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).

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Data Warehouse Server(Tier 1)

DataWarehouse

OperationalData Bases

SemistructuredSources Query/Reporting

Data Marts

MOLAP

ROLAP

Clients(Tier 3)

Tools

MetaData

Data sources

Data(Tier 0)

IT

Users

BusinessUsers

Business Users

Data Mining

Archiveddata

Analysis

OLAP Servers(Tier 2)

ExtractTransformLoad (ETL)

www data

Putting the pieces togetherPutting the pieces together