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Building a Data Warehouse with SQL Server. Presented by John Sterrett. About Me…. AITP - Pittsburgh. What is a data warehouse?. Building a Data Warehouse with SQL Server. What is Business Intelligence?.

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aitp pittsburgh

AITP - Pittsburgh

what is a data warehouse

What is a data warehouse?

Building a Data Warehouse with SQL Server

what is business intelligence

What is Business Intelligence?

According to Wikipedia BI refers to skills, technologies, applications and practices used to help a business acquire a better understanding of its commercial context.

The following is a definition from Business Intelligence with Microsoft Office PerformancePoint Server 2007

Business intelligence (BI) is more of a concept than a single technology. The goal is to gain insight into the business by bringing together data, formatting it in a way that enables better analysis, and then providing tools that give users power—not just to examine and explore the data, but to quickly understand it.

business problems that bi addresses

Business Problems that BIAddresses

Slow-to-execute queries

General system slowdowns

Manual query writing

Disparate data sources

Data is not available to all users

Too much data

what is bi to the users

What is BI to the users?

BI is fast to query.

BI improves your return on investment (ROI)

BI is a tool that allows users to find what they need.

business cases

Business Cases

A technology department could analyze work completed for departments and/or clients. This could then be used to estimate future flat fee engagements, establish seasonal hiring, balance overtime.

A medical center could use statistics covering a wide range of lab values and a large number of patients to identify whether a patient currently being treated might be at an elevated risk for a certain types of disease.

Application that’s great for data entry but lacks in depth reporting and drilldown capabilities.

A company who wants to centralize data to a single data source for allowing decision makers the ability to make decisions as needed.

what products are involved

What Products Are Involved?

Database Technologies

SQL Server 2005/2008 (Database Engine)

SQL Server Analysis Services (SSAS)

SQL Server Integration Services (SSIS)

User Interface Technologies

SQL Server Reporting Services (SSRS)

SQL Server Management Studio (SSMS)

Performance Point 2007





Browse a Cube using Management Studio

goals for dimensional modeling

Goals for dimensional modeling

Understand star schema

Understand dimensional modeling

Understand changing dimensions

Understanding fact (or measure) and cube modeling

star schema

Star Schema…

A star schemaconsists of at least one fact table and a number of dimension tables.

Star Schema is highly recommended schema for SSAS cubes.

facts and measures

Facts and Measures

Fact table consists of at least two types of data: keys and measures.

Keys are usually surrogate keys that link to the dimension tables.

Measuresare numeric values that are usually additive that express business metrics.



Dimensions describe who, what, when, where and why for the facts.

Dimensions should consist of the following data types

Surrogate key.

Primary key of the loaded source(s)

Any additional attributes (columns) that describe the business entity.



Hierarchies serve two purposes:

Convenience for end users.

Provides drill down / drill up features

where do i go from here

Where do I go from here?

Create Use Grain Statements

What are the key metrics for your business?

What factors do you use to evaluate those key metrics?

What level of granularity do you use evaluate each factor?

grain statement examples

Grain Statement Examples:

We want to see time worked, hours billed, and cost of work by date, by employee, by department, by location, and by projects.

We want to see sales amount and sales quantity by day, by product, by employee, and by store location.

We want to see average score and quantity of courses taken, by course, by day, by student, by manager, by curriculum, and by curriculum type.



Build a Cube

extracting loading data

Extracting & Loading Data

*The process of extracting, transferring and loading data consumes about 75% of the Data Warehouse project.

It is highly recommended to use SSIS for ETL instead of native T-SQL

so you are interested in building a data warehouse

So… You are interested in building a Data Warehouse

Click here to download a Virtual PC that includes sample Data Warehouses and all of Microsoft’s BI tools.

If you already have SQL Server 2005 and Analysis Services configured click here to download samples (Click here for SQL Server 2008)

Check out this Introduction to Data Warehousing with SQL Server









Foundation of SQL Server 2005 Business Intelligence.

Business Intelligence with Microsoft Office PerformancePoint Server 2007

ACM – Intro to Data Warehousing