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SoftwareTestingo » Interview Questions » Data Warehouse (DWH) Interview Questions

Data Warehouse (DWH) Interview Questions

Last Updated on: November 21, 2021 By Softwaretestingo Editorial Board

What We Are Learn On This Post

  • Data Warehouse Interview Questions

Data Warehousing Interview Questions: We have seen there are so many searches happening in most of the search engines so we are preparing some of the frequently asked Data Warehousing Interview Questions in the interview. For the Data Warehouse Interview, we will also provide you with some Unix, Linux, and Windows skills questions depending on the MS SQL server.

In this article, we will go through some of the most common questions that you can expect to see in a data warehousing interview. These are usually pre-requisites to a job for any position in a data warehouse or ETL team.

Data warehousing is a collection of techniques that allow data from different sources to be stored and processed in a systematic way. It has become an essential part of business intelligence (BI) and decision support systems (DSS). This article will provide you with some common questions asked during interviews for a data warehouse position.

Data Warehouse Interview Questions

  • What is a data warehouse?
  • What are Data Marts?
  • What is a Star Schema?
  • What is Dimensional Modeling?
  • What is Snow Flake Schema?
  • What are the Different methods of loading Dimension tables?
  • What is the Difference between OLTP and OLAP?
  • What is ETL?
  • What are the various ETL tools in the Market?
  • What are the various Reporting tools in the Market?
  • What is a Fact table?
  • What is a dimension table?
  • What are modeling tools available in the Market? Name some of them?
  • What is Normalization? First Normal Form, Second Normal Form, Third Normal Form?
  • What is ODS?
  • Which columns go to the fact table and which columns go to the dimension table?
  • What is the level of Granularity of a fact table? What does this signify?
  • How are the Dimension tables designed? De-Normalized, Wide, Short, Use Surrogate Keys, Contain Additional date fields and flags.
  • What are slowly changing dimensions?
  • What are non-additive facts? (Inventory, Account balances in bank)
  • Whatareconformeddimensions?
  • What are SCD1, SCD2, and SCD3?
  • Discuss the advantages & Disadvantages of star & snowflake schema?
  • What is a junk dimension?
  • What is the difference between view and materialized view?
  • Compare Data Warehousing Top-Down approach with Bottom-up approach
  • What is the fact less fact schema
  • What is the confirmed dimension
  • What is the architecture of any Data warehousing project? What is the flow?
  • What is ODS? What data was loaded from it? What is DW architecture?
  • Where do we use Star Schema & where is Snowflake?
  • What r the advantages and disadvantages of a star schema and snowflake schema.
  • What are semi-additive measures and fully additive measures
  • Tell me what would the size of your warehouse project?
  • What is the surrogate key? where we use it explain with examples
  • Can a dimension table contain numeric values?
  • What is the Difference between E-R Modeling and Dimensional Modeling?
  • Why fact table is in normal form?
  • How is Data in the data warehouse stored after data has been extracted and transformed from heterogeneous sources
  • What is the role of surrogate keys in a data warehouse and how will u generate them?
  • What is meant by metadata in the context of a Data warehouse and how it is important?
  • What is the main difference between Inmon and Kimball’s philosophies of data warehousing?
  • How do you connect two fact tables? Is it possible?
  • What are the steps to build the data warehouse
  • What is data cleaning? how is it done?
  • Difference between DWH and ODS?
  • Explain Additive, Semi-additive, Non-additive facts?

Conclusion:

Data warehousing is an important part of data analysis. If you want to land a job in this field, it’s important that you know the right questions to ask during your interview. This blog post has outlined some key questions you should be asking at the interview stage. Read through them and learn how to ace your next data warehousing interview!

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