Adamson & Venerable Chapter 2 & working out a Homework 5/6 Solution

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Adamson &amp; Venerable Chapter 2 &amp; working out a Homework 5/6 Solution. Transforming Relational Databases into Dimensional Diagrams Spring 2012. Dimensional modeling in Sales. In a DW designed to analyze SALES data, important component of a dimensional model is the Product Dimension.

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### Adamson & Venerable Chapter 2 &working out a Homework 5/6 Solution

Transforming

Relational Databases into Dimensional Diagrams

Spring 2012

Dimensional modeling in Sales
• In a DW designed to analyze SALES data, important component of a dimensional model is the Product Dimension.
• Product dimension includes important characteristics used to differentiate the product in the marketplace, called Discriminators.
• Discriminators: Descriptive characteristics of a product that further describe it and are relevant to purchasing decisions. Tracking discriminators allows the business analyst to monitor performance of various product styles, influencing production and marketing plans.
• Discriminators for a men’s suit: Cloth, color, style/cut, weight, size
• Discriminators for vehicles: Model name, model styling package, line, category, exterior color, model year, interior color
Other Dimensions in Sales
• Time dimension: Time key, month, day, date, year, day of week, quarter.
• Customer_Demographic dimension: This does not require a row for each customer, but groups customers by different combinations of age, gender, income, and geography. The degree of demographic segmentation varies by industry.
• Dealer dimension: Data on dealer performance are needed, to support decisions on which dealers should be eased out of business.
• Method_Of_Paymentdimension (lease, financing options, etc.)
Fact Table: Storing derived facts
• A commonly used derived fact should be stored, and not calculated in reports and queries. Cutting such “redundant” key measures from the fact table results in the following:
• Development of reports gets more complex
• Increased potential for errors in reports
• Increased documentation requirements
• A Hundred dollars’ worth of disk space is saved (40 MB of space savings for a 10-million row fact table)
Transformation Stages(Key for Homework #5/6)
• De-normalization Process
• Determine Dimensions and Fact Tables
• Delete Relationships
• Rebuild Tables
• Rebuild Relationship Diagram as Star Diagram, a.k.a., Dimension Table
• Provides information needed to complete Homework 6, too!
Premiere Products ERD

Redrawn to form most

likely Star Diagram

Rebuild Tables
• Using copied operations database
• Be sure all ops. data is saved and backed up … multiple times.
• Data staging & cleansing
• Denormalize extra relationships
• Order:OrderLine;
• Customer:SalesRep;
• Order:OrderLine  OrderDetail
• Customer:SalesRep  OrderDetail
• Transform data for new tables in Access: Make Table
• Export data files, if needed, to rebuild elsewhere (Excel)
• Additional Transformations as needed in Excel
• Create the Time dimension
• Re-Import data files to new tables
OrderDetail Query

Order of Columns

Not critical

Sort order not critical but

Good time to revise

OrderDetail Table

Set Primary Keys

Build Star Diagram

Fact Table

What’s Missing?

Time Dimension

Use SQL to eliminate

Redundant dates

Excel Time Table
• Create Time table using
• Excel Formulas:
• Fill
• Copy/paste
• Compute Quarter
• Conversion Formulas
• Etc.
PP -- Relation List

Fact Table

• OrderDetail[OrderNum, PartNum, OrderDate, CustNo, RepNo, NumOrdered, Price]

Dimension Tables

• Customer[CustNum, CustName, Street, City, State, Zip, Balance, CreditLimit]
• Rep[RepNum, LastName, FirstName, Street, City, State, Zip, Commission, Rate]
• Part[PartNum, Desc, OnHand, Class, Warehouse, Price]
• Time[TimeKey, Day_of_Week, Month, Year, JulianDate, Quarter, etc.]
http://www.webopedia.com

• Short for Globally Unique Identifier, a unique 128-bit number that is produced by the Windows OS or by some Windows applications to identify a particular component, application, file, database entry, and/or user. For instance, a Web site may generate a GUID and assign it to a user's browser to record and track the session. A GUID is also used in a Windows registry to identify COMDLLs. Knowing where to look in the registry and having the correct GUID yields a lot information about a COM object (i.e., information in the type library, its physical location, etc.). Windows also identifies user accounts by a username (computer/domain and username) and assigns it a GUID. Some database administrators even will use GUIDs as primary key values in databases.
• GUIDs can be created in a number of ways, but usually they are a combination of a few unique settings based on specific point in time (e.g., an IP address, network MAC address, clock date/time, etc.).
Tools/Analyze/Documenter

OrderDetail table

HB -- Relation List

Fact Table

• BookTrans[BookCode, AuthorNum, BranchNum, Sequence, PubCode, OnHand, InventoryDate]

Dimension Tables

• Book[BookCode, Title, Type, Price, Paperback]
• Publisher[PubCode, PubName, City, …State, Zip]
• Author[AuthorNum, LastName, FirstName, …]
• Branch[BranchNum, BranchName, Location, Employees]
• Time[TimeKey, Day_of_Week, Month, Year, JulianDate, Quarter, etc.]
Summary
• Complete Transformations
• How normal are the resulting tables?
• 1NF, 2NF, 3NF?
• Document Transformation maps
• Prepare for Appending Tables with new data
• Tools/Analyze/Documenter (next time)