Raw Data vs. Business Information

„ Capturing Raw Data

z Gathering data recorded in everyday operations Module 1: Introduction „ Deriving Business Information z Deriving meaningful information from raw data

to Data Warehousing „ Turning Data into Information and OLAP z Implementing a

OLTP Source Systems Characteristics

„ OLTP System Characteristics „ Provides Data for Business Analysis Processes z Processes real-time transactions of a business „ Integrates Data from Heterogeneous Source Systems z Contains data structures optimized for entries and edits „ Combines Validated Source Data z Provides limited decision support capabilities „ Organizes Data into Non-Volatile, Subject-Specific „ OLTP Examples Groups

z Order tracking z Service-based sales „ Stores Data in Structures that Are Optimized for Extraction and Querying z Customer service z Banking functions

z Point-of-sales

Data Warehouse System Components ‹ Defining OLAP Solutions

Data Warehouse User Data Data Marts Data Access Sources Staging Area „ OLAP

„ Common OLAP Applications

„ Relational Data Marts and OLAP Cubes

„ OLAP in SQL Server 2000

Data Input

Data Access

1 OLAP Databases Common OLAP Applications

„ Executive Information Systems „ Financial Applications

„ Optimized Schema for Fast User Queries z Performance measures z Reporting

„ Robust Calculation Engine for Numeric Analysis z Exception reporting z Planning z Analysis „ Conceptual, Intuitive Data Model

„ Multidimensional View of Data „ Sales/Marketing Applications „ Operations Applications

z Drill down and drill up z Booking/billing z Manufacturing

z Product analysis z Customer service z Pivot views of data z Customer analysis z Product cost

Relational Data Marts and OLAP Cubes OLAP in SQL Server 2000

RelationalRelational OLAPOLAP CubeCube „ Microsoft Is One of Several OLAP Vendors DataData MartMart „ Analysis Services Is Bundled with Microsoft SQL Server RelationalRelational N-dimensionalN-dimensional DataData StorageStorage DataData StructureStructure DataData structurestructure 2000

DetailedDetailed andand „ Analysis Services Include DataData ContentContent SummarizedSummarized DataData SummarizedSummarized DataData z OLAP engine RelationalRelational andand RelationalRelational andand DataData SourcesSources z technology Non-relationalNon-relational SourcesSources Non-relationalNon-relational SourcesSources

FastFast PerformancePerformance forfor FasterFaster PerformancePerformance forfor DataData RetrievalRetrieval DataData ExtractExtract QueriesQueries DataData ExtractExtract QueriesQueries

‹ Understanding Data Warehouse Design The Employee_Dim EmployeeKeyEmployeeKey EmployeeIDEmployeeID ...... „ The Star Schema

„ Components Dimension Table Time_DimTime_Dim Fact Table Product_Dim „ Dimension Table Characteristics TimeKeyTimeKey Sales_FactSales_Fact ProductKeyProductKey TheDateTheDate TimeKeyTimeKey ProductIDProductID „ The ...... EmployeeKeyEmployeeKey ...... ProductKeyProductKey CustomerKeyCustomerKey ShipperKeyShipperKey SalesSales AmountAmount UnitUnit SalesSales ......

Shipper_Dim Customer_Dim ShipperKeyShipperKey CustomerKeyCustomerKey ShipperIDShipperID CustomerIDCustomerID ......

2 Fact Table Components Dimension Table Characteristics

DimensionDimension TablesTables sales_fact Table

customer_dimcustomer_dim 201201 ALFIALFIAlfreds Alfreds Foreign Keys Measures

customer_keycustomer_key product_keyproduct_key time_keytime_key quantity_salesquantity_sales amount_salesamount_sales product_dimproduct_dim 201 25 134 400 10,789 2525 123 123 Chai Chai

„ Describes Business Entities

time_dimtime_dim „ Contains Attributes That Provide Context to Numeric 134134 1/1/20001/1/2000 Data The grain of the sales_fact table is defined by the lowest level of detail stored in each dimension „ Presents Data Organized into Hierarchies

The Snowflake Schema ‹ Understanding OLAP Models

„ OLAP Components

„ OLAP Dimensions vs. Relational Dimensions

„ Dimension Fundamentals

„ Dimension Family Relationships

„ Cube Measures „ Defines Hierarchies by Using Multiple Dimension Tables „ Relational Data Sources „ Is More Normalized than a Single Table Dimension

„ Is Supported within Analysis Services

OLAP Database Components OLAP Dimensions vs. Relational Dimensions

OLAP Relational

„ Numeric Measures REGION „ Dimensions REGION West West „ Cubes CA East OR East STATE REGION MA CA West NY OR West MA East NY East

3 Dimension Fundamentals Dimension Family Relationships

‹ USA is the parent of North West and USA South West North West ‹ North West and South West are Oregon children of USA Washington ‹ North West and California are South West descendants of USA California ‹ North West and USA are ancestors of Washington ‹ North West and South West are siblings ‹ Oregon and California are cousins ‹ All are dimension members

Cube Measures Relational Data Sources

„ Star and Snowflake Schemas „ Are the Numeric Values of Principle Interest z Are required to build a cube with Analysis Services „ Correspond to Fact Table Facts „ Fact Table „ Intersect All Dimensions at All Levels z Contains measures „ Are Aggregated at All Levels of Detail z Contains keys that join to dimension tables „ Form a Dimension „ Dimension Tables

z Must exist in same database as fact table

z Contain primary keys that identify each member

‹Applying OLAP Cubes Defining a Cube

„ Defining a Cube

„ Querying a Cube Atlanta

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Working with Dimensions and Hierarchies Visualizing Cube Dimensions

„ Dimensions Allow You to

z Slice z Dice „ Hierarchies Allow You to

z Drill Down z Drill Up

Connecting to an OLAP Cube Review

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Sales Units 6000 „ Introducing Data Warehousing

Level 02 5000 Year „ Defining OLAP Solutions Quarter 4000 Sheri Now mer - 2001 - Quarter 4 Sheri Now mer - 2001 - Quarter 3 „ Understanding Data Warehouse Design 3000 Sheri Now mer - 2001 - Quarter 2 Sheri Now mer - 2001 - Quarter 1 2000 Sheri Now mer - 2000 - Quarter 4 „ Understanding OLAP Models Sheri Now mer - 2000 - Quarter 3 1000 Sheri Now mer - 2000 - Quarter 2 „ Sheri Now mer - 2000 - Quarter 1 Applying OLAP Cubes 0 Bagels Muffins Sliced Bread Cheese Deli Meats Frozen Chicken

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