1. Designing a Data Warehouse from the Ground Up
Dustin Ryan
Data Platform Architect

2. Dustin Ryan Designing analytics solutions for past 10+ years
Currently Data Platform Solution Architect for Microsoft for past 3+ years
Blogs at SQLDusty.com
Author, technical editor, speaker
Facebook.com/SQLDusty
Twitter.com/SQLDusty
Baby wrangler and chicken farmer
Live in Jacksonville, Florida with my wife, Angela, and three kiddos, Dallas, Bradley, Andrew
LinkedIn.com/in/SQLDusty
YouTube.com/dustinryan

3. Why a Data Warehouse? OLTP Data Warehouse Purpose
Execution of business
Analysis of business
Primary Interaction
Single transaction
Aggregated transactions
Interaction Method
Insert, Update, Delete
Select
Temporal Focus
Current
Current/historic
Design Optimization
Update concurrency
High-performance queries
Design Principle
3NF
Star Schema

4. Four Steps Identify the business process Identify the grain
Choose the dimensions
Choose the measures

5. Identify the Business Process
Business process NOT business department
If just starting, choose high impact, low risk area of the business
The business can help you here
For this example  Retail Sales
High
Impact
Low
Impact
Low
Risk
High
Risk

6. Identify the Grain What does one fact row represent?
Choose the most atomic level
We can’t predict the queries!
“One row represents a movie rented by a customer from an employee in a store on a day.”

7. Define the Dimensions Who, what, where, when?
De-normalized design focuses on high performance reads
Best attributes are descriptive
Use smallest data type possible

8. Define the Measures How the business measures success
Best measures are fully additive
Non-additive measures should be handled in SSAS

9. Resources

10. http://tinyurl.com/DesignDWGroundUp Dustin Ryan
Facebook.com/SQLDusty
Twitter.com/SQLDusty
Dustin Ryan
Data Platform Solution Architect
SQLDusty.com
LinkedIn.com/in/SQLDusty
YouTube.com/dustinryan