Wednesday, January 23, 2008

“Other” member in Data Visualization

One important and fabulous thing that I learned from "Data Analysis Using SQL and Excel" book is how I can represent correct data using correct SQL query.
Imagine that we have an orders table in which we have customer’s orders. Now we need to present the following query:
What is the distribution of the number of orders in the 5 states that have the largest number of orders? (By representing the Other‘s as a other category)



Friday, January 4, 2008

Analyzing vs. Designing

I want to describe the difference between "Data Mining with SQL Server 2005" and "Data Analysis Using SQL and excel" in general.
This difference is derived from the distinction between analyzing and designing data mining systems.
For analyzing a Data Mining system, you must use some tools that have the potential of rapid development, in order to interact with the stakeholders and users quickly. In this situation, I recommend using Excel and SQL to clarify the results for users, due to the fact that, in this situation there is not any implemented mining model on OLAP server.
But if you are designing a Data Mining system, you must have a good knowledge of the OLAP server and the development tools that it has.
As a result, I think the “Data Mining with SQL Server 2005" suits for Designing, while the "Data Analysis Using SQL and excel" is appropriate for Analyzing.

I prefer to read both of these books, in order to handle the analyst and designer roles in a BI project, Maybe it is because of the fact that, I could not find anyone who can do one of these roles.
But I prefer to read the “Data Analysis Using SQL and excel” at first, then involve in “Data Mining with SQL Server 2005”.
I think it is worth to buy “Data Analysis Using SQL and excel”, but I have not any idea about the other book, but it is not so important, because there are not any other books which describe Data mining with SQL Server 2005, practically.
Finally, I do not think these books can be used instead of each other. In fact, they must be used as complementary.