It's almost Nov 4th and we have record voter turnout for early voting. While all of this is fine and dandy, I wonder if there is auditing in place on voters, when and where they voted etc, and are there checks and balances in place on ensuring no voter fraud occurs. If not, the next president will need to make that a US Government CIO's task to be implemented. We being a largely advanced nation in terms of technology cannot afford to be ignorant about this.

This election as such is historic enough already and we do not want additional attractions added to the same. The rest of the world is watching us.

Running a long distance marathon. Well as a matter of fact, if you look at any data warehouse project, the key ingredient to the success of the project is the "endurance" of the team. Building a data warehouse is not a trivial task, you have people, politics and personalities to deal with, apart from tight deadlines, data issues like master data, metadata and data quality, business intelligence needs that surpass the capabilities of what is available, budget issues etc.

Managers often tend to overlook the "endurance" of the team. We often see projects fail due to nothing else but "burn outs". If you observe the marathon runners, they train differently for the marathon across their schedule. A data warehouse team is no different, they need to perform at different speeds at the various phases.

Like the poem "water water everywhere", we seem to be inundated with appliances everywhere from every vendor. That is a lot of information to digest. In the coming months, to educate the users and decision makers alike on the technologies and which to choose and how to implement them, I'm teaching a course at TDWI New Orleans on Nov 7th, and will be holding an independent seminar series in three cities. More information on the three cities will be announced shortly. Keep checking my blogs.

As I start this blog, I thank Teradata for inviting independent analysts like myself and others in the team to their Partners Conference at Las Vegas.

Teradata has announced the availability of flavors of data warehouse appliances. Yes you heard me correct, a data warehouse appliance. Wait a minute, Teradata had pioneered this concept years ago, so what is new? well if you think long enough, Teradata has identified itself to be an enterprise player and had always defined its vision to be the solution to the enterprise data warehouse. That vision is still strong and intact, but as an answer to the competition (In the kick off session on Monday, Mike Koehler CEO and Stephen Brobst CTO of Teradata mentioned this statement) in the area of the data warehouse appliance, Teradata now has a series of "purpose built platforms" that can provide scalable and robust solutions.

Dear Readers,

In the spate of recent announcements from Oracle and HP about the Oracle-HP Database Machine and Exadata storage, I found some time to catch up with Foster Hinshaw, widely acknowledged as the Father of the Data Warehouse Appliance. Here are a few excerpts from our conversation:

Krish: Foster, in your opinion as the pioneer of data warehouse appliances, where does Oracle’s offering fit?
Foster: Krish, I have a very high regard for Larry Ellison and Oracle, but I feel that the Oracle is playing catch-up with the rest of the industry in this space. The technology is at least five-years-old and will need to mature fast.

Krish: Interesting observation. With the current growth rates in the industry, where is the real opportunity for data warehouse appliances in general and Dataupia in particular?
Foster: Well, the growth we are talking about is two fold, data is growing at 50% every year and users are growing by 30%. In this growth spurt, data warehouse appliances can offload the workload from the core database, thereby improving the overall system performance. Dataupia’s mission statement is “free your data,” and we believe in architecting solutions which will offer the users the scalability and flexibility to use their data from their data warehouse to achieve business performance.

Krish: Another key point that I have always advocated is the overall cost of the implementation. Your thoughts?
Foster: Yes, that is correct, whenever we talk about cost savings, we should account for the overall solution cost including implementation and ongoing maintenance. Our goal with Dataupia is to enable the scalability while maintaining the cost at a stable level from both the implementation and the infrastructure perspective.

Krish: One last question, is the Oracle-HP database machine truly MPP? In my opinion this is an underlying qualification to be considered an appliance. Whether MPP is in the software layer or the hardware layer, it still is the glue. How would you compare Dataupia and Oracle’s newest offering in this aspect?
Foster: Interesting opinion. Oracle’s new appliance is a solid first step toward full MPP. When we talk about MPP, we’re talking about data manipulation that is handled on multiple storage notes so that the user gets the benefit of complete data manipulation. At this stage, Oracle’s version is a light weight model of MPP in that it begins to put some, but not all, operations in parallel. Large data warehouse require extensive data movement and manipulation which is why Dataupia has and will continue to make MPP a core focus of their appliance.

If you are interested to see more excerpts from this discussion, please leave your comments and we will post more from this discussion.