Answer / sreenu329

One of the most interesting and valuable dimensions in a
data warehouse is one that explains why a fact table record
exists. In most data warehouses, you build a fact table
record when something happens. For example:

When the cash register rings in a retail store, a fact
table record is created for each line item on the sales
ticket. The obvious dimensions of this fact table record
are product, store, customer, sales ticket, and time.
At a bank ATM, a fact table record is created for every
customer transaction. The dimensions of this fact table
record are financial service, ATM location, customer,
transaction type, and time.
When the telephone rings, the phone company creates a fact
table record for each "hook event." A complete call-
tracking data warehouse in a telephone company records each
completed call, busy signal, wrong number, and partially
dialed call.
In all three of these cases, a physical event takes place,
and the data warehouse responds by storing a fact table
record. However, the physical events and the corresponding
fact table records are more interesting than simply storing
a small piece of rev enue. Each event represents a
conscious decision by the customer to use the product or
the service. A good marketing person is fascinated by these
events. Why did the customer choose to buy the product or
use the service at that exact moment? If we only had a
dimension called "Why Did The Customer Buy My Product Just
Now?" our data warehouses could answer almost any marketing
question. We call a dimension like this a "causal"
dimension, because it explains what caused the event.

Answer / sreenu329

One of the most interesting and valuable dimensions in a
data warehouse is one that explains why a fact table record
exists. In most data warehouses, you build a fact table
record when something happens. For example:

When the cash register rings in a retail store, a fact
table record is created for each line item on the sales
ticket. The obvious dimensions of this fact table record
are product, store, customer, sales ticket, and time.
At a bank ATM, a fact table record is created for every
customer transaction. The dimensions of this fact table
record are financial service, ATM location, customer,
transaction type, and time.
When the telephone rings, the phone company creates a fact
table record for each "hook event." A complete call-
tracking data warehouse in a telephone company records each
completed call, busy signal, wrong number, and partially
dialed call.
In all three of these cases, a physical event takes place,
and the data warehouse responds by storing a fact table
record. However, the physical events and the corresponding
fact table records are more interesting than simply storing
a small piece of rev enue. Each event represents a
conscious decision by the customer to use the product or
the service. A good marketing person is fascinated by these
events. Why did the customer choose to buy the product or
use the service at that exact moment? If we only had a
dimension called "Why Did The Customer Buy My Product Just
Now?" our data warehouses could answer almost any marketing
question. We call a dimension like this a "causal"
dimension, because it explains what caused the event.

Answer / dipali

amazing explaination...thanks a lot

Answer / sorna kumar muthuraj

Interstingly i noticed now only it is not casual... it is
CASUAL dimension... Now the name makes more sense with the
explanation... Cool Explanation dude...

Answer / anonymus

good copy of the link :)

http://www.kimballgroup.com/html/articles_search/articles199
6/9611d05.html

Answer / bsgsr

i sincerely appreciate ur interest n moreover ur patience
in explaining so beautiful. thanks a million for ur ans.
can i have your mail id or number pls.
here are mine.
9866188658 bsgsr12@gmail.com

Hi All, I have three question. 1) How to remove the header and footer in a flat file in informatica? 2)How to load the first and last record of flat file into the target? 3)I have a Input and Output table. Input Name Salaray Month A 100 Jan A 200 Feb A 300 March B 400 April B 500 May B 600 June Output Name Salaray Month A 100 Jan A 300 Feb A 600 March B 400 April B 900 May B 1500 June How to implement and get the ouput as mentioned above. If Possible kindly provide the SQL query also. Kindly any one help to implement this concept. Thanks, Pradeep

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