This document summarizes different approaches to data warehousing including Inmon's 3NF model, Kimball's conformed dimensions model, Linstedt's data vault model, and Rönnbäck's anchor model. It discusses the challenges of data warehousing and provides examples of open source software that can be used to implement each approach including MySQL, PostgreSQL, Greenplum, Infobright, and Hadoop. Cautions are also noted for each methodology.

1. Open Source Data Warehousing:
MySQL and Beyond
Alex Meadows
Twitter: @DBA_Alex
Percona MySQL University
Raleigh, NC
1/29/2013

2. What Is Data Warehousing?
● Central repository
● Oriented on Reporting and Analysis
● Integrates multiple sources
● Core to Business Intelligence and Advanced
Analytics
● Helps keep source systems clean and lean

3. Warehouse Methodologies
● Inmon’s 3NF/Hub and Spoke Model
● Kimball’s Conformed Dimension Model
● Linstedt’s Data Vault Model
● Rönnbäck’s Anchor Model/6NF

4. Source: http://www.anchormodeling.com/wp-content/uploads/2011/05/Anchor-Modeling-GSE.pdf

5. Common DW Challenges
● Data storage increases significantly
● Time based snapshots
● Storing source changes
● Massive queries
● Joining many tables, from multiple sources
● Exploratory vs reporting
● Source Issues Magnified
● Scalability

6. Inmon’s 3NF Model
● Original data warehouse model
● Move historical data into own data store
● Data transformed to 3NF
● Entities and relationships

7. Open Source Software
● MySQL
● PostgreSQL
● Greenplum (PostgreSQL derivative)
● Any other traditional RDBMS

8. Cautions
● Indexing
● Replication
● Partitioning

9. Kimball’s Conformed Dimensions
● Normal database modeling does not meet needs of
reporting and analysis
● Denormalize data
● Dimensions
● How does data need to be filtered?
● Facts
● What are we wanting to analyze/measure?

10. Source: http://blog-mstechnology.blogspot.com/2010/06/bi-dimensional-model-star-schema.html

11. Open Source Software
● Greenplum (PostgreSQL derivative)
● InfiniDB (MySQL derivative)
● Infobright (MySQL derivative)
● Other columnar data stores

12. Columnar Data Stores
● Designed for conformed dimensions
● High Performance
● Self-indexing based on usage
● High compression of data

13. Row vs Columnar Databases
Source: http://dbbest.com/blog/column-oriented-database-technologies/

14. Cautions
● Traditional RDBMS
● Not built for conformed dimensions!
● Performance will become issue

15. Inmon’s Hub and Spoke
● Combines
● 3NF central data warehouse
● Conformed dimensions
● Becomes foundation for further variants

16. ● Linstedt’s Data Vault Model
● Mixes 3NF and Conformed Dimensions
● Model data per business entities and their
relationships
● Hubs
● Store unique business entity identifiers (keys)
● Links
● Relate hubs and other links to form relationships
● Satellites
● Store unique information regarding entity or
relationship

17. Source: http://danlinstedt.com/about/data-vault-basics/

18. Cautions
● While you get the best mix between 3NF and
conformed dimensions, data marts are still needed
● Issues seen with both 3NF and conformed
dimensions can be found here

19. Open Source Software
● MySQL
● PostgreSQL
● Greenplum
● Other Traditional RDBMS
● NoSQL
● Hadoop

20. ● Rönnbäck’s Anchor Model/6NF
● Focus is on the data and it’s relationships.
● Anchors
● Model entities and events
● Attributes
● Model properties of anchors
● Ties
● Model relationships between anchors
● Knots
● Model relationships between shared properties

21. Source: http://en.wikipedia.org/wiki/Anchor_Modeling

22. Cautions
● Number of joins will be an issue for some databases
● Queries will become complex
● Joins
● Finding properties/valuable information
● Every column in traditional tables becomes own
unique table

23. ?

24. Open Source Software
● Anchor Modeling website
● http://www.anchormodeling.com
● Web based design tools
● No databases built specifically for 6NF