Top 50 Data Warehousing Interview Questions with Answers

This article attempts to explain the fundamental rudimentary concepts of data warehousing in the form of questions and their respective answers. After reading this article, you should gain good enough knowledge on various concepts of data warehousing.
A data warehouse is a electronical storage of an Organization's historical data for the purpose of analysis and reporting. According to Kimpball, a datawarehouse should be subject-oriented, non-volatile, integrated and time-variant.

What is the benefits of data warehouse?

Historical data stored in data warehouse helps to analyze different aspects of business including, performance analysis, trend analysis, trend prediction etc. which ultimately increases efficiency of business processes. 

Why Data Warehouse is used?

Data warehouse facilitates reporting on different key business processes known as KPI. Data warehouse can be further used for data mining which helps trend prediction, forecasts, pattern recognition etc.

What is the difference between OLTP and OLAP?

OLTP is the transaction system that collects business data. Whereas OLAP is the reporting and analysis system on that data.
OLTP systems are optimized for INSERT, UPDATE operations and therefore highly normalized. On the other hand, OLAP systems are deliberately denormalized for fast data retrieval through SELECT operations.
Explanatory Note:

In a departmental shop, when we pay the prices at the check-out counter, the sales person at the counter keys-in all the data into a "Point-Of-Sales" machine. That data is transaction data and the related system is a OLTP system. On the other hand, the manager of the store might want to view a report on out-of-stock materials, so that he can place purchase order for them. Such report will come out from OLAP system

What is data mart?

Data marts are generally designed for a single subject area. An organization may have data pertaining to different departments like Finance, HR, Marketting etc. stored in data warehouse and each department may have separate data marts. These data marts can be built on top of the data warehouse.

What is ER model?

ER model is entity-relationship model which is designed with a goal of normalizing the data.


Sample Questions from next page ...
1. What is dimensional modeling?
2. What is dimension?
3. What is fact?
4. What are additive, semi-additive and non-additive measures?
5. What is Star-schema?
6. What is snow-flake schema?
7. What are the different types of dimension?
And many more high frequency questions!