In about two weeks from now, at the Enterprise Data World, I will be teaching a course on Data Warehouse Architectures, covering both older and newer data warehouse architectures and associated implementations.

I will answer questions on the subject both at that conference and the upcoming TDWI conference in Chicago where I'm teaching on "DW Performance Tuning" and "Requirements Gathering from an IT perspective"apart from two other courses on infrastructure.
If you are going to TDWI Chicago and are yet to get approval, send me an email and get a discount code for 35% discount on your conference fees.

Coming back to the subject from yesterday on Data Warehouse Architecture, it is interesting to see both executive and technical level people asking the same question - "what did we do wrong with our data warehouse?".  My word of advise again is, look for a pragmatic and practical approach to architect and design the data warehouse. Following a text book will only take you half way to the journey. Remember that you deal with people, process and technology to build the data warehouse. Cutting corners anywhere in these areas will result in the "tower of babel" or another "leaning tower of pisa".

Starting next week, I plan to post blogs on Analytics and implementing successful analytical platforms, post questions or ideas that you would like to discuss.

Where are we going with "The Data Warehouse"? this is a million dollar question. When everybody started building a data warehouse, the goal was a consolidated version of truth and an enterprise data repository. Then we moved on to build layers of applications and called it business intelligence. From all this chaos we delivered another vision with master data and metadata management.

Among all these issues and discoveries, somewhere we have created a series of stovepipes in the data warehouse environment. Fast forward to today, we are looking at "consolidation" of all the different silos into one data warehouse. To me it looks like we are running behind a tiger by holding its tail. How do we get this right? there is no one architecture that will fit everybody's needs nor is there one methodology that will answer every facet of developing and deploying a data warehouse for all situations.

Looking at the bigger picture, it is clear that everybody who has followed any architecture or methodology has implemented "their" own version of the methodology or altered some facet of the implementation to suit their needs. One can argue that it was the right thing to do. But on introspection, if we had paid some extra time to the architecture efforts, we could have avoided some mistakes. Well better late than never.

As we move to re-build and build new data warehouses, let us look at what we need

• Business Case
  
• Strong Methodologies - CIF, CIFE, DW2.0, DW Lifecycle, BI Pathway any of these are good methodologies
• Robust Roadmap - A strong roadmap to build the subject areas for the data warehouse is needed
• Robust data architecture
• Robust testing framework
• Business Applications
• USERS

If you need more information on any sibject area, you can check the following

BeyeNETWORK - for more general information
TDWI - the upcoming Chicago conference has dedicated courseware on this subject
DAMA - the DAMA conference next month has dedicated courseware on this subject

There are several fellow experts of mine who have published books on this subject. Before you use a book to follow the implementation, ensure that you have all the other material mentioed here available. Remember as Jack Welch said - "the team with the best players wins", empower yourself and your teams with the right knowledge and approach. By selecting the right architecture and approach, you can make the build and test cycles more manageable and possibly have cycles to extend the implementation to topics like MDM

I will be starting a forum on this network on "DW Architectures" soon, please post topic of interest to start discussions on.

Last week's announcement from IBM regarding the acquisition of Sun Microsystems, shows that we are not done with the buying spree yet. What are the benefits of this meger or acquisition?

If you see the market, Sun has very little server presence, compared to the Storage segment, Java, MySQL and the Open Cloud announcement. This will mean

• IBM can now extend its presence to the lower end of the market
• IBM can play in the MySQL space, and have a strong presence in integrating their Appliance portfolio
• IBM can have a stronger play in the Storage space
• IBM can have a large presence in the Open Cloud opportunity
• IBM can leverage the SAAS model for applications
• IBM will be the universal controller of JAVA - this is huge.
• A good chance of MapReduce being adopted by IBM
• Virtualization and Server consolidation will get a newer IBM offering
• There will be only IBM, HP and DELL left in the server market in the enterprise space

Well the list can go on and on. What does Sun get from the deal? it gets a strong "global" partner. Sun can augment the lower end and mid-size offerings from IBM well and of course the current partnerships that Sun has with Appliance vendors like Greenplum will be in question or maybe even extended to newer levels at IBM/SUN.


Well it is an interesting play that we will watch with great interest.