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Data Warehousing Interview Questions

1)   What do you know about Datawarehousing ?
Data warehousing is used for reporting and analysis of the data. It is primarily used to analyze data. Some of the additional uses of it are extraction and retrieval of data, manage, load and manipulate data. It has various tools which can transform, load, extract and manage the data.

2)   State some of the benefits of dataware housing?
These are some of the benefits of dataware housing they are: -
1)   Regardless of the data source it provides common data model this feature makes analysis of data much easier.
2)   Inconsistency is identified during the loading process.
3)   In case there is a crash of the database, database programmer can feel comfortable because it is stored in the dataware housing.
4)   It is very efficient and will not slow down the operational system.

3)   What are the different interconnected layers of a dataware house?
There are four different interconnected layers they are: -
•   Operational database layer
•   Informational access layer
•   Data access layer
•   Meta data layer.

4)   Explain about the top design?
In a top design model data ware house is designed in a normalized enterprise model. This is chiefly used for business intelligence and management capabilities. Data used for business purpose and management can be met through a dataware house. It is used to generate dimensional views and is known to be good and stable against business changes.

5)   Explain about the time variant feature of Dataware housing?
Dataware house detects and tracks all the changes according to time. This allows a database developer to detect the changes across time which helps him to keep a log.

6)   Explain about the non-volatile feature of dataware house?
Data once written and saved in dataware house is static and it can never be deleted and over written once confirmed. It will be static and read-only. This can be used for future reporting and it allows good security feature.

7)   Explain some disadvantages of dataware house?
These are some of the disadvantages of dataware house: -
1)   It represents a very large project with a very broad scope which is a big disadvantage.
2)   Upfront costs are very huge and the duration of the project from the start to the end user is significant.
3)   It is inflexible and unresponsive to the departmental needs.

   Explain about hybrid design model?
Due to the various risks and disadvantages presented by top down and bottom down models it has become imperative that Hybrid methodologies be used. This is used for fast turn around time and enterprise wide data consistency. This uses features and benefits from top down and bottom down models.

9)   Explain about the bottom up design?
Bottom up design provides the advantage of a quick turnaround. As soon as the first data marts are created business values can be returned. Some of the disadvantages caused are due to multiple versions and false truth operations. Conforming dimensions and tight management can mitigate these risks.

10)    State some of the disadvantages of data ware houses?
Some of the disadvantages are as follows: -
1)   Dataware house can be costly due to high maintenance of the database. It is usually not static.
2)   There is always a risk of it delivering outdated results which makes it less productive.
3)   A fine line exists between dataware house and operational systems.

11)    What do you think about the future of dataware housing?
Dataware housing will be used by organizations to analyze their huge pool of data. With the development of various dataware house appliances performance of dataware housing applications can be improved. There would be many more apps working in accordance with the Gartner Group report which makes it much user friendly and reliable.

12)    What are the general stages of use of dataware house?
These are the general stages of use: -
1)   Offline operational database
2)   Offline dataware house
3)   Real time dataware house
4)   Integrated dataware house.

These are some of the questions which might be asked they are: -
1)   Explain the hierarchy of dataware house?
2)   State differences between reusable transformation and Mapplet?
3)   Explain about IQD file and Cognos script editor?

4)   State two major differences between a dataware house and operational dataware house?
There exist two major differences they are: -
1)   It integrates information from a pre existing source database
2)   It is used for analysis usually for OLAP where huge amounts of data occur frequently.
5)   Explain about the integrated dataware house stage?
At this stage dataware house gets updated every time a transaction occurs. The transactions performed during this time are passed back to the operational systems which records the transactions.