Welcome to Class Guys , Well , we will be starting our week of by taking a sneak peek into SQL BI gearing up to the more elaborative and deep understanding about BI and its applications .

Before , just diving in , I would like to mention here , the useful resources , which are being referred here up in this article.

1. SQL Server Books Online (http://msdn.microsoft.com/en-us/library/ms130214.aspx)

Jorge had written about the Sql server books online , and its availability in his article ,which can be found on http://sqlchicken.com/2009/09/sql-university-basic-tools/

2. http://www.sqlauthority.com

First of all , a general question I would like to answer about BI .

Q . What is BI and what exactly it is there for ?

Answer : BI Stands for Business Intelligence .

We’ll make it little bit mathematical

BI=Business Intelligence

BI = Business + Intelligence

      Business= (Enterprise , Customary,etc)

      Intelligence= Decision

                  Decision = Data and Analysis

                           Analysis = Skills + Processes + Technologies + Tools(applications)

BI = (Enterprise,Customary,etc) + (Data and analysis)

So, now from above equation its clear that BI Means Analysis of Enterprise/customary Data .

Now , just summing up the above equation in words , BI basically refers to Processes,Skills,Applications,Technologies that are use to support the Decision making Process.

BI Technologies : When we do talk about BI Technologies , then its not just about reporting , but its lot more than reporting .

Just to explain about why BI is lot more than reporting , I would like to state here an live example ( going out of boundaries of BI and sql server) , of ICEBERG . when we see an iceberg , its 10% above the sea water while 90% beneath , so that’s the same thing with Reports , reports are only the visualization of that 90% of what is beneath it i.e a lot things including , Data , OLAP , Text mining ,Querying , Statistical analysis ,Benchmarking ,Predictive Analysis .

Summing up the above we got to know a new equation

BI = Reporting + Data mining + OLAP +Text mining + Benchmarking + Statistical analysis + Predictive Analysis + Querying .

Its Well Said by Danny Siegel about BI , that an effective BI system provides corporations with “one version of the truth”.

What BI is for ?

BI is there for Success of a business , because it helps you in making decisions and when you are able to make correct , accurate decisions on time then only the success is yours . Because if BI is there , then you are handy with your statistical analysis and predictive analysis (future , foreseen analysis) and can better make your decisions to remain competitive and stay ahead .

Hopes , the question we had started off with is answered and we are quite clear about the concept of BI.

Now , another Question Comes out to mind .

Q. What is the History of BI  ? Where all it came from ?

Answer : A basic question , what is the history of BI , how it came into existence and from where it get evolved , is it something new born ??

No , its not something which is recently evolved but today it is used more and more that’s why we are wondering and taking it as some new born , but its nothing like that ,

In a 1958 article, IBM researcher Hans Peter Luhn used the term business intelligence. He defined intelligence as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

In 1989 Howard Dresner (later a Gartner Group analyst) proposed BI as an umbrella term to describe “concepts and methods to improve business decision making by using fact-based support systems.”. It was not until the late 1990s that this usage was widespread.

Wow , so above we came to know that BI do exists there since from a very long time , but today it is widespread and is present everywhere ,no matter whatever the business is , whatever the technology is , if some system is there , decision is there , BI is THERE .

Now comes another question :

Q. If BI is so vast , then from where to start with .?

Answer : Anywhere , that totally depends upon your choice , you can go for data mining , OLAP ,Text mining , Reporting , that all is your part , you need to decide what best you can do , because there are lots of tools available under BI , but you had to choose which tools you wish to learn , use and master .

Another tricky question :

Q. What language(terminology) does BI Speaks ?

Answer : Sure , that’s very important to learn the BI Language(Terminology) , because unless and until we are familiar with BI Terminology , we won’t be able to get hands on it , so just a quick view of BI Terms :

Aggregation : Information stored in summarized form

Agent : Application (client ) who searched the data and sends the alert.

Alert : Message sent by agents

Attribute : Fields or columns in table ,report ,charts .

Cube : Known as multidimensional format used for viewing and analyzing data .The fundamental structure for data in a multidimensional (OLAP ) System.

Data : Reality , facts stored in and processed.

Data Base : Collection of data

Data Cleansing / Scrubbing : Removing erroneous data

Data Mart : Local Data Warehouse , Small subset of Data warehouse for one or few divisions

Data Migration : Process of moving of data from one environment to other

Data Mining : Digging deep the hidden relationship of data and attributes among each other

Data Transformation : Process after data migration is done ,i.e the step of modifying the data as per the new data warehouse.

Data Warehouse : A storage of Enterprise/ customary data meant for to be analyzed .

Drill down and drill up : Process to move across hierarchy used in OLAP.

ETL : Extract , transform and load makes ETL . i.e get the data , transform it(modify) and migrate it .

DTS : its below ETL , because it’s a tool for ETL .

Star Schema : The simplified database as per the normalized forms of database management system

Fact Table : the table containing :

1. The fields storing the foreign keys which connect each particular number to the appropriate value in each dimension.
2. The fields storing the individual number, measure or any numeric value. Example(discount,price,etc)

Measure : A numeric value in fact table

Multidimensional Analysis / OLAP =Online Analytical processing, the technique to process and fetch out results in different –different dimensions of data i.e cubes .(widespread use of graphs and spreadsheets )

Slice : Tool for OLAP Viewing of data through multi dimensions example : Where clause in OLAP.

Dice : Tool for OLAP Viewing of data through multi dimensions

Replication : Replica of one data at another place.

Schema : Logical arrangement of data within database.

MDX : Multidimensional expressions, the query language for OLAP ,

Hopes , now ,as we have discussed couple of basic questions about BI ,we are ready with to get dive into the BI sea , but before getting in it , we’ll have a break and will continue on this interactive session in the same manner (if nobody complains of this is not a good idea to learn about what BI is .?) .

While writing this article , I was just wondering up from where to start this article on , because it is such a vast area to discuss on with that I cannot see the boundaries of , then thought of , why not to make it more interactive in an question / answer manner . I myself started asking questions to me as a layman and then tried to answer the questions .Hope you’ll enjoy this question answer class of BI , not to mention here , that if you do have any question up there in mind that is not covered up or required some more lights , then do revert back , I am waiting for your questions and would try my best to answer them .

You can reach me at govindsyadav[@]soliddotnet[dot]com