Data warehouse interview questions assess a candidate’s knowledge and understanding of data warehousing concepts, technologies, and practices. These questions may cover a wide range of topics, such as data modelling, ETL (Extract, Transform, Load) processes, data integration, data quality, data governance, and data analytics.
Some common interview questions may include describing the differences between a data warehouse and a database, explaining the importance of data profiling and cleansing, and discussing how to design an effective data warehouse schema.
It’s important to prepare for these types of interview questions by studying the fundamentals of data warehousing and practising with sample questions to help you articulate your understanding of these complex concepts.
Data Warehouse Interview Questions
- What is a data warehouse?
- What are Data Marts?
- What is a Star Schema?
- What is Dimensional Modeling?
- What is the Snowflake 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 modelling tools are available on 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 the 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 a 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 is a fact table 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 is it 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?
- What is the difference between DWH and ODS?
- Explain Additive, Semi-additive, and Non-additive facts.
Conclusion:
Data warehousing is an important part of data analysis. To land a job in this field, you must know the right questions and answers to ask during your interview. This blog post has outlined some key questions you should ask at the interview stage. Read through them and learn how to ace your next data warehousing interview!
