90+ Data Modeling Interview Questions and Answers

You should never go into an interview unless you are completely prepared. And if you're preparing data modeling interview questions, you've come to the right place.

Data modeling is the process through which data models are created to store data in the database. To prepare you for the upcoming interview, we have listed some of the most commonly asked data modeling interview questions.

If you are preparing for a tech interview, check out our technical interview checklist, interview questions page, and salary negotiation e-book to get interview-ready!

Having trained over 13,500 software engineers, we know what it takes to crack the most challenging tech interviews. Our alums consistently land offers from FAANG+ companies. The highest ever offer received by an IK alum is a whopping $1.267 Million!

At IK, you get the unique opportunity to learn from expert instructors who are hiring managers and tech leads at Google, Facebook, Apple, and other top Silicon Valley tech companies.

Want to nail your next tech interview? Sign up for our FREE Webinar.

To give you a better understanding of what type of data modeling interview questions you can expect based on your experience, in this article, we’ll be covering:

• Basic Data Modeling Interview Questions
• Intermediate Data Modeling Interview Questions
• Advanced Data Modeling Interview Questions
• Additional Data Modeling Interview Questions
• FAQs on Data Modeling Interview Questions

Basic Data Modeling Interview Questions

For freshers, the following data modeling interview questions for data engineers need to be prepared:

Q1. What is data modeling?

The process of building a model that stands for the data and the relationship between different data to store it in a database is called data modeling. This skill is helpful across all domains such as data engineering, data science, software development, etc.

It helps in preparing, analyzing, and processing data by continuously reorganizing, restructuring, and optimizing it to meet the needs of the company.

Q2. List the benefits of data modeling.

The primary benefits of data modeling are:

• Decrease in the number of errors during software development.
• Better performance of the application as well as the database.
• Mapping data between different processes of a company has become easier.
• Increases the speed of database design at the conceptual, physical, and logical levels.
• Helps reduce maintenance costs as the system grows at a large scale.

Q3. What is a data model? Name its types.

The information schema that helps in the sorting and normalization of different components of information and establishes relations among them is called a data model. Such models also become tables in the database that can be retrieved and then processed on the basis of the company’s needs.

The three kinds of data models are:

• Conceptual data model
• Physical data model
• Logical data models

Q4. What is the full form of ERD?

ERD is the short form of Entity Relationship Diagram. It is a logical entity representation and defines relationships among entities. These entities stay in boxes, and arrows symbolize relationships.

Q5. Define denormalization and its purpose.

The technique where redundant data is added to a database that’s already normalized is called denormalization. The purpose is to enhance the read performance by sacrificing the write performance.

Sample Data Modeling Interview Questions for Freshers:

1. Define a surrogate key.
2. Name the critical relationship types in a data model and describe them.
3. Explain the fact and fact table.
4. What is the fact less fact?
5. What do you mean by in-memory analytics?
6. Explain the function of a primary key constraint.
7. What is meant by normalization and denormalization?
8. What is an enterprise data model?
9. Define granularity.
10. What is data sparsity?
11. What is meant by dimension in data?
12. Define hashing.
13. What is cardinality?
14. What does the data model contain?
15. Explain:

• Logical data model and logical data modeling
• Physical data model and physical data modeling

16. Elaborate on the following terms:

• Table (entity)
• Column (attribute)
• Row

17. What is meant by relational data modeling?
18. Differentiate between a logical and physical data model.
19. What do you mean by foreign key constraint and composite foreign key constraint?
20. Explain dimension and attribute.
21. Differentiate between OLTP and OLAP.
22. What is a check constraint?
23. What are the different types of normalization?
24. Elaborate on PDAP.
25. Explain analysis service.
26. What is a sequence clustering algorithm?
27. What is meant by discrete and continuous data?
28. Explain the time series algorithm.
29. What is meant by a self-recursive relationship?
30. Define the following:

• Check constraint
• Index
• Data scheme
• Sequence
• Data mart
• Data warehousing

31. Explain the OLTP system and list some examples.
32. What is data mining?
33. What is predictive modeling analytics?
34. What do you mean by RDBMS?
35. Define XMLA.

Intermediate Data Modeling Interview Questions

When applying for intermediate-level roles, these are the data modeling interview questions for data engineers you can expect:

Q1. List the most common errors that can occur when doing data modeling.

The most common errors that can occur during data modeling are:

• Creating overly-broad data models: When the tables are running higher than 200, the data model becomes more and more complex. Thus, it increases the chances of failure.
• Unrequired surrogate keys: Surrogate keys are needed only when the natural key can’t fulfill its role as the primary key.
• Absence of a purpose: Many times, the user has no idea about the business’s goal or mission. While it’s not impossible, it is difficult to create a specific business model if the modeler doesn’t have the required understanding.

Q2. What are the two different design schemas?

The two design schema is known as the Star schema and Snowflake schema. The former has a fact table centered and has multiple dimension tables that surround it. The latter is similar; only the level of normalization is higher and results in it looking like a snowflake.

Q3. Define a slowly changing dimension.

The dimensions used to coordinate the historical and current data in data warehousing are known as slowly changing dimensions. Its four types are — SCD Type 0 through SCD Type 3.

Q4. Explain subtype and supertype entities.

Entities can be divided into sub-entities based on sub-entities and grouped according to specific features. Every sub-entity has its own attributes, and each is known as a subtype entity.

Some attributes are specific to every entity and are placed in a higher or super-level entity. This is the reason why they’re called supertype entities.

Q5. What is the importance of metadata in data modeling?

Known as “data about data,” Metadata is the data that covers the different types of data present in the system and what it’s used for, and who uses it.

Sample Intermediate Data Modeling Interview Questions

1. What is business intelligence?
2. What are conceptual data models and conceptual data modeling?
3. Explain the bit-mapped index.
4. What is an identifying and non-identifying relationship?
5. Define the Critical Success Factor and list its four types.
6. Differentiate between star schema and snowflake schema.
7. Explain the main types of relationships in a data model.
8. What is meant by an object-oriented database model?
9. List the disadvantages of the hierarchical data model.
10. How many null values can be inserted in a column that has a unique constraint?
11. Explain the different types of constraints.
12. What is meant by UML?
13. How do you handle recursive relationships, and why are they bad?
14. What are the disadvantages of using data modeling?
15. What is a network model?
16. Differentiate between the primary key and foreign key.
17. What is the significance of using keys?

Advanced Data Modeling Interview Questions

If you’re an experienced professional, do go over the following data modeling interview questions for data engineers:

Q1. Do all databases need to be rendered in 3NF?

The answer is no; it’s not a requirement. However, denormalized databases can be easily accessed, are easy to maintain, and are less redundant.

Q2. Why are NoSQL databases more useful than relational databases?

NoSQL databases have the following pros:

• Structured, semi-structured, and non-structured data can be stored in them.
• They have a dynamic schema which means it evolves and changes whenever needed.
• These have sharding. This process helps split up and distribute data to smaller databases for faster access.

Q3. Define a junk dimension.

It refers to a grouping of low-cardinality attributes such as indicators and flags, removal from other tables, and then “junked” into an abstract dimension table. Often they are used to initiate Rapidly Changing Dimensions in the data warehouses.

Q4. What is meant by confirmed dimension?

When a dimension is confirmed, it is attached to a minimum of two fact tables.

Q5. What are recursive relationships?

These types of relationships happen when there is a relationship between itself and an entity. Recursive relationships are complicated and need more complex approaches to mapping the data to a schema.

Sample Advanced Data Modeling Interview Questions

1. Define a data model repository.
2. How would you differentiate between forwarding and reverse engineering in the data model context?
3. When a unique constraint gets applied to a column, does it generate an error if you attempt to place two nulls in it?
4. Define the importance of the first and third normal forms.
5. What is a non-computer example of preemptive and non-preemptive scheduling?
6. How does data sparsity affect aggregation?
7. Differentiate between the hashed file stage and the sequential file stage in relation to DataStage Server.
8. What is an artificial (derived) primary key, and how is it used?
9. Explain the second and fourth normal forms.
10. Give some rules for the third normal form.
11. What is meant by an alternate key?
12. What is the rule of the fifth normal form?
13. List the characteristics of a database management system.
14. Differentiate between a data mart and a data warehouse.
15. What is a bi-directional extract?

Additional Data Modeling Interview Questions

1. Explain data collection frequency.
2. List the different kinds of cardinal relationships.
3. What is meant by hierarchical DBMS?
4. What is a data-modeling tool?
5. Elaborate on the process-driven approach of data modeling.
6. Explain the two types of data modeling techniques.
7. What is a compound key?
8. List out popular DBMS software.
9. What are the advantages and disadvantages of the data model?
10. Explain the different kinds of fact tables.
11. What is an aggregate table?
12. List the types of hierarchies in data modeling.
13. What is meant by chained data replication?
14. What is virtual data warehousing?
15. Explain snapshot of data warehouse.

We hope the questions listed above have given you an insight into the type of data modeling interview questions you can expect for data engineers. If you’re intrigued by data modeling and want to build a career in it, read Career Path to Become a Successful Data Scientist.

FAQs on Data Modeling Interview Questions

Q1. What are data modeling techniques?

Data modeling techniques, as well as methodologies, are used for the purpose of modeling data in a standard, consistent, and predictable manner so that it can be used as an effective resource.

Q2. What is a data model?

A data model is used to segregate different data elements and organize them to understand how they relate to one another and other real-world entity properties.

Q3. What qualities are needed in a good data model?

The four definite qualities required are — data is easily consumable, major data changes in the data model are scalable, give a predictable performance, and can adapt to the required changes but without compromising on the first three qualities.

Q4. What is data modeling?

The process that leads to the creation of a model for storing data in a particular database is called data modeling. It is the conceptual representation of data objects and defines the relationship between different data objects as well as the rules.

Q5. What are the three major components of a data model?

The three major components of a data model are — data structures, operations on data structures, and integrity constraints for operations and structures.

Q6. What are some important data modeling interview questions for data engineers?

Some important data modeling interview questions for data engineers are — Define normalization. What are the different types of data models? What is the full form of ERD? What do you mean by a surrogate key?

Preparing for Data Modeling Interview Questions?

If you’re looking for guidance as you prepare Data Modeling interview questions, sign up for our free webinar.

Interview Kickstart offers interview preparation courses taught by FAANG tech leads and seasoned hiring managers. We have trained thousands of software engineers to crack the most challenging interviews at Google, Facebook, Amazon, Apple, Netflix, and other top tech companies.

Register for our FREE webinar to learn more!

‍