Data WarehousingData Warehousingand its Importance and its Importance

in MNCsin MNCs

A producer wants to knowA producer wants to know

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Which are our lowest/highest margin

customers ?

Which are our lowest/highest margin

customers ?

Who are my customers and what products are they buying?

Who are my customers and what products are they buying?

Which customers are most likely to go to the competition ?

Which customers are most likely to go to the competition ?

What impact will new products/services

have on revenue and margins?

What impact will new products/services

have on revenue and margins?

What product prom--otions have the biggest

impact on revenue?

What product prom--otions have the biggest

impact on revenue?

What is the most effective distribution

channel?

What is the most effective distribution

channel?

Data, Data everywhereData, Data everywhere• An MNC can’t find the data it needs

o data is scattered over the networko many versions, subtle differences

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MNC can’t get the data it needs need an expert to get the data

MNC can’t understand the data found available data poorly documented

MNC can’t use the data found results are unexpected data needs to be transformed from one

form to other

What are the users What are the users saying...saying...

• Data should be integrated across the enterprise

• Summary data has a real value to the organization

• Historical data holds the key to understanding data over time

• What-if capabilities are required

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What is a Data What is a Data Warehouse?Warehouse?

A single, complete and consistent store of current and historic data, obtained from a variety of different sources, and made available to end users in a way they can understand and use in business context.

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What is Data What is Data Warehousing?Warehousing?

A process of transforming data into information and making it available to users in a timely enough manner to make a difference.

Technique for assembling and managing data, (from various sources) for the purpose of answering business questions. Thus making decisions that were not previous possible

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Data

Information

Warehouses are very Large Warehouses are very Large Data BasesData Bases

• Terabytes -- 10^12 bytes:

• Petabytes -- 10^15 bytes:

• Exabytes -- 10^18 bytes:

• Zettabytes -- 10^21 bytes:

• Zottabytes -- 10^24 bytes:

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Walmart -- 24 Terabytes

Geographic Info. Systems

National Medical Records

Weather images

Intelligence Agency Videos

Data Warehouse PropertiesData Warehouse Properties

o Subject Oriented

o Used to analyze business

o Summarized and refined

o Snapshot data

o Integrated Data

o Ad-hoc access

o Knowledge User (Manager)

o Thousands of Users

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Components of the Components of the WarehouseWarehouse

• Data Extraction and Loading

• The Warehouse

• Analyze and Query -- OLAP Tools

• Metadata

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Data Warehouse Data Warehouse ArchitectureArchitecture

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Data Warehouse Engine

Optimized Loader

ExtractionCleansing

AnalyzeQuery

Metadata Repository

RelationalDatabases

LegacyData

Purchased Data

ERPSystems

Data Warehouse and Data Data Warehouse and Data

MartsMarts

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OLAPData MartLightly summarizedDepartmentally structured

Organizationally structuredAtomicDetailed Data Warehouse Data

From the Data Warehouse From the Data Warehouse to Data Martsto Data Marts

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DepartmentallyStructured

IndividuallyStructured

Data WarehouseOrganizationallyStructured

Less

More

HistoryNormalizedDetailed

Data

Information

Application AreasApplication Areas

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Industry ApplicationFinance Credit Card AnalysisInsurance Claims, Fraud Analysis

Telecommunication Call record analysisTransport Logistics managementConsumer goods promotion analysisData Service providersValue added dataUtilities Power usage analysis

Thank You!!!Thank You!!!

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A Presentation by:A Presentation by:

Abhitanjay Chaudhary (C23)Abhitanjay Chaudhary (C23)Owais Ashraf (C41)Owais Ashraf (C41)

Anant Prakash Gupta (C24)Anant Prakash Gupta (C24)Rajat Sharma (C20)Rajat Sharma (C20)