As i look around at some of the leading companies across the globe, I find a state of chaos across these companies, especially in information management. What is interesting to note is that the problem transcends Fortune 100 to Small Business and is very similar. Where did things go wrong? all these companies have spent valuable dollars to improve information management.

Deeper investigation reveals several gaps and loopholes. The vendors that came to provide strategy and technology services addressed "point in time" problems and developed focused solutions. With the craziness of technology improvements, market conditions (m&a), business changes all coming together, the entire situation is like playing "poker" at the high stakes tables in Vegas.

How do we unravel from the state of chaos to a state of order. Hiring more strategy consultants is not the only answer. We need to do a holistic overview of the business situation and find out where issues have come from and how the current solution process will address today and the future.

In order to recover from a state of chaos to clarity, you need to look at the strength of the organization and its people, assess its technological prowess, its competition, business value, market value, strategic maturity and adoption of processes in the organization and more.

However doing all this in a short span requires a great deal of focus and more maturity from the vendor that will be hired for this exercise. Size does not matter in this spectrum.

A vendor rating from the Analyst community is a starting edge of this process, but that alone is not enough, we need to ask for organization maturity, delivery capability and much more to not repeat the mistakes to get to a state of chaos. Sometimes a few "niche" vendors may be needed to solve the larger problem.

To be continued.....

We all know by now the word "columnar database" and some of the most popular providers - ParAccel, Vertica and Infobright. Though columnar databases have distinct performance advantages and applications that can be deployed, from a business perspective, there was a question mark and doubts of where to apply these solutions.

In my opinion, the unstructured data integration into the data warehouse is a very key area of applicability for the Columnar database. The reason for this statement, stems from the fact that the unstructured database is a very column oriented data store and if we are processing oodles of text, the reference of information will be more clustered in nature. This drives the need to store the data in a co-located manner, which then leads me to look at columnar databases more closely.

I do not imply that Oracle, SQL Server, DB2 or Teradata cannot support the unstructured database needs, but for those who want to adopt to the cloud, use more on demand scalability etc, columnar databases may be an in-house option. Additionally for those providers in cloud arena, columnar databases may be more optimal to adopt to.

I'm currently running tests on Infobright and will share the results in the next few days. I'm processing a large volume of semi-structured and unstructured data and will measure the throughput and performance against the standard RDBMS platforms.

In my technical opinion, choosing a columnar database for processing large textual data provides more business benefits, the final results can be migrated to a corporate environment, but operational aspects can be done in the columnar platform.

I have been researching on this subject for the past few months. It is becoming clear that to control errors in diagnosis and treatment of medical conditions, Evidence Based Medicine can be defined as "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of the individual patient. It means integrating individual clinical expertise with the best available external clinical evidence from systematic research." (Sackett D, 1996).

This requires research and processing of clinical information that can be leveraged by a Doctor. While search from Google, Oracle and others are supporting the search portions, Clinical data is heavily semi-structured - a combination of structured and unstructured data. The unstructured portions is where you have all the content and context of diagnosis, treatments, prognosis, conclusions etc. This is where Textual ETL and the unstructured database build will help us. The entire DW2.0 methodology can be directly applied to this system. We can classify, categorize, contextualize and capture information from the clinical data into a database.

In conducting the research, I have found that we can process years of clinical data into an unstructured database with relative ease and when combined with the statistical research data, the results have been an eye-opener. The possibilities of reducing errors and offering the right treatment means the cost of healthcare can be managed well. The quality of the treatment will be more rewarding and welcome.

I know that many Doctors and other medical professionals have different opinions on this subject, but that was when no technology was available to support EBM, now that we do, we should start paying attention to this area.

I will be writing my first article for this year on this subject, stay tuned for the article.