Conformed dimension

conformed dimension:

A conformed dimension is a dimension that should has the same meaning and content when being referred to different fact tables. It can be refer to any number of fact tables in multiple data marts.If two dimension tables to be considered as conformed, they must be identical to each other. There shouldn't be any other type of difference between the two dimension tables.

Why Conformed Dimension?

As we discussed in characteristics of Data warehouse, it should maintain integrity. It is nothing but tight integration between different type of dimension tables. Conformed dimensions help us to make the tightly coupled integration between different dimensions

other wise it will lead to stove pipe data warehouse.

Example:

Customer dimension is the well know example for conformed dimension, because sales and product facts can be refer to the same dimension for different purpose. Because the customer who are using our product will be available in customer dimension and the list of customer who purchased our product is also available in same customer dimension.

If you have any quires please make comment.

Data warehousing basics

What is Data Warehouse:
Data warehouse is a relational database which is used to store as well as analyze the historical data of an organization(s). It usually contains the historical data derived from transactional data of single source system or different source systems. The main purpose of the data warehouse is to serve the reporting needs of higher management.

We can say simply in other words, Data warehouse is a database which contains the integrated data of the different source systems.

Characteristics of a data warehouse: 

1) Subject Oriented: A data warehouse can be used to analyze the particular subject area like HR,Sales,Marketing.

2) Integrated: As we discussed data warehouse is collection of data from different data source, so it should avoid the conflicts like different data types,different type of metrics like that.
Suppose data is collecting from different countries, in this case each country have its own currency standards like rupee,dolor,euro etc.. but when data warehouse storing this data it should store in unique format.

3) Nonvolatile:  As name indicates, once data entered into data warehouse it should not be changed. Because we are using data warehouse for historical data analysis.

4) Time Variant: A data warehouse's focus on change over time is what is meant by the term time variant. Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse. This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a data warehouse can hold all addresses associated with a customer.

DAC 11G Installation on Windows 7 64 Bit:

DAC 11G Installation on Windows 7 64 Bit:

1) Download DAC 11g from oracle official site. (OTN)

2) Then extract the ZIP folder.

3) Open the DAC folder then double click on the DAC setup.exe

4) Click on Next.

5) Provide the root directory of informatica powercenter.

6) Provide the proper path for domin.infa file as shown in above screenshot.

7) Select the destination path for DAC installation folder. Make sure there is no spaces between the folder name, otherwise it will cause installation error futrher.

8) Select any radio button as your wish, and then click on next.

9) Once check the Pre-Installation summary and click on Install button.

10) Installation in progress, it will take a while.

11)  We have installed the DAC software successfully. :) :)

Now it's time to configure the DAC.

Click here for DAC configuration.