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Chapter 2 - Video # 4

What's the Difference Between a Data Warehouse and a Data Mart?

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Chapter 2: Business Intelligence & Data Warehousing with SSASCourse: SQL Server 2008/R2 Analysis ServicesCourse Id: 165Presented by Scott Whigham

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• A data warehouse is a layer of abstraction over a company’s data that provides a single point of access for queries and reports– Most organizations have data spread out across

many systems

– The data warehouse unifies these underlying systems into a single interface

Data Warehouse

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Data Warehouse

Data entry Data warehouse Reporting Training

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• Without a data warehouse, reporting would be more challenging:– The Oracle accounting system stores country as “USA”

– The SQL Server Help Desk system stores country as “U.S.”

– The MySQL web store stores country as “United States”

Data Warehouse

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• The data warehouse simplifies reporting– The Oracle ERP system stores country as “USA”

– The SQL Server Help Desk system stores country as “U.S.”

– The MySQL web store stores country as “United States”

Data Warehouse

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• There are other advantages to creating a unified view of an organization’s data:– Agreed-upon definition of terms and algorithms

– Can apply data quality and consistency procedures during loading of DW

Data Warehouse

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• There are at least two types of data warehouses– Data warehouses that store detail information

– Data warehouses that store pre-calculated aggregates

• Let’s compare!

Data Warehouse

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• Data warehouses that store detail information:– Typically copy records from underlying data

sources on a 1:1 basis

– Often used for both analysis and archival purposes

– When a user wants to aggregate, must write aggregate expressions

Data Warehouse

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• When a user wants to aggregate, must write aggregate expressions:

SELECT p.ProductName

, COUNT(*) AS Orders

, SUM(sd.UnitsOrdered) AS UnitsSold

FROM Sales.InternetSales s

JOIN Sales.InternetSalesDetail sd

ON s.OrderId = sd.OrderId

JOIN Products.Product p

ON sd.ProductId = p.ProductId

WHERE YEAR(s.OrderDate) = 2011

GROUP p.BY ProductName

ORDER p.BY ProductName

Data Warehouse

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• Data warehouses that store pre-calculated aggregates:– During the loading of the DW, various levels of

aggregations are calculated and stored in the data warehouse

• “Sales” would be pre-aggregated by month, quarter, year

• “Customer growth” by city, state/province, country

– Used only for analysis

Data Warehouse

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• When a user wants to view aggregations, he/she simply asks for the data

SELECT ProductName, Orders, UnitsSold

FROM DataWarehouseTable

WHERE OrderYear = 2011

WHERE OrderYear = 2011

AND Quarter = 1

WHERE OrderYear = 2011

AND Month = 10

Data Warehouse

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• Regardless of the type of data warehouse, data quality is important– Garbage in, Garbage Out

Data Warehouse

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• Typically a data warehouse is not changed directly by the users– The DW is loaded from the underlying data sources

– Users change the underlying data sources

Data Warehouse

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• The data warehouse may not be in sync with the data entry systems– If the data warehouse is loaded each Sunday,

reports run on Saturday will not feature the previous week

Data Warehouse

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• Typically the BI Architects define update schedules– Updating/loading the data warehouse requires

connecting to each data source and uploading changes into the data warehouse

– If updating the data warehouse can be done in less than 6-8 hours, most shops opt for nightly updates

Data Warehouse

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• The term data mart can be confusing– Typically a data mart is a subset of the data

warehouse that holds data related to a specific area

• Sales

• Products

• Billing

Data Warehouse

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• However it is possible to have only a data mart– A data warehouse holds data across many

departments

– Your organization may only wish to start with a “Billing” data mart

• If it is successful, you will add others and build a data warehouse

Data Warehouse

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• OLTP vs. OLAP

"Always end the name of your child with a vowel, so that when you yell the name will carry.“

Bill Cosby

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