Subscribe

RSS Feed (xml)

Powered By

Skin Design:
Free Blogger Skins

Powered by Blogger

search topic

Thursday, April 17, 2008

Data Warehouse Interview-8

What are the Different methods of loading Dimension tables? Conventional Load:
Before loading the data, all the Table constraints will be checked against the data.

Direct load:(Faster Loading)
All the Constraints will be disabled. Data will be loaded directly.Later the data will be checked against the table constraints and the bad data won’t be indexed.

What is conformed fact? Conformed dimensions are the dimensions which can be used across multiple Data Marts in combination with multiple facts tables accordingly

What are Data Marts? Data Marts are designed to help manager make strategic decisions about their business.
Data Marts are subset of the corporate-wide data that is of value to a specific group of users.
There are two types of Data Marts:
1.Independent data marts – sources from data captured form OLTP system, external providers or from data generated locally within a particular department or geographic area.
2.Dependent data mart – sources directly form enterprise data warehouses.

What is a level of Granularity of a fact table? Level of granularity means level of detail that you put into the fact table in a data warehouse. For example: Based on design you can decide to put the sales data in each transaction. Now, level of granularity would mean what detail are you willing to put for each transactional fact. Product sales with respect to each minute or you want to aggregate it upto minute and put that data.

How are the Dimension tables designed? Most dimension tables are designed using Normalization principles upto 2NF. In some instances they are further normalized to 3NF.
Find where data for this dimension are located.
Figure out how to extract this data.
Determine how to maintain changes to this dimension (see more on this in the next section).

What are non-additive facts? Non-Additive: Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table.

What type of Indexing mechanism do we need to use for a typical datawarehouse? On the fact table it is best to use bitmap indexes. Dimension tables can use bitmap and/or the other types of clustered/non-clustered, unique/non-unique indexes.
To my knowledge, SQLServer does not support bitmap indexes. Only Oracle supports bitmaps.

No comments: