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Top 50 Data Modeling Interview Questions and Answers [2022]

Posted in Data Science
Data Modeling Interview Questions

Table of Contents

Data modeling creates a clear, visual picture of a software system and its data pieces using symbols and language to represent the data. Programmers working with data modeling collaborate with other IT professionals, like data scientists and administrators to model complex data. Those models play a vital role in an organization’s decision-making process. 

But how do those professionals start their careers? It all starts with preparing for interview questions on data modeling

If you’re planning to pursue a data modeling career, your first step is to nail that interview. We’ll walk you through common data modeling interview questions for you to review and practice!

Data Modeling Interview Questions and Answers for Beginners, Experienced, and Advanced Roles

Not all data modeling roles have the same expectations. We’ll break down our list of data modeler interview questions by difficulty: basic, intermediate, and advanced. 

1. How do you define data modeling?

Data modeling visually represents a complicated software system’s design and data using text and symbols to denote the data flow’s direction.

2. Describe facts and fact tables.

A fact is a representation of numerical data. For instance, the due net amount. A fact table includes foreign keys from dimensional tables together with numerical data.

3. List various data modeling design schemas.

The three main types of design schemas are as follows: 

  • Star Schema
  • Snowflake Schema
  • Galaxy Schema

4. When should you account for denormalization?

You should account for denormalization when your table is heavily involved. This will help you build a data warehouse. 

5. What is the factless fact table?

A fact table is referred to as factless if it simply contains key values and no measurable facts.

6. Define the terms attribute and dimension.

Dimensions represent qualitative data. You’ll often see textual and descriptive features in dimension tables.

7. What is in-memory analytics?

In-memory data analytics is a scenario where the slower disk access is completely eliminated so you can access all data to be processed from the main memory. 

8. What is data sparsity?

Data sparsity is a collection of data with a large number of zero values and a small number of non-zero values.

9. What is the composite primary key?

A composite primary key is a collection of columns that serve as primary keys for a table. 

10. What is the primary key?

A primary key is a column or a collection of columns unique to every table row. Primary key values cannot be empty or NULL. Each table has at least one primary key. 

11. What is a table in databases?

Data is kept in rows and columns and organized into tables. Columns, usually referred to as fields, display data vertically aligned. The horizontal alignment of data is represented by rows, often known as a record or tuple.

12. What is a data mart?

A data mart is like a simplified form of a data warehouse.

13. What are the different types of fact tables?

The following are the different types of fact tables:

  • Additive: Measure that can be integrated into any dimension
  • Non-additive: Measure that cannot be added to any other dimension
  • Semi-additive: Measure can only be integrated into a few dimensions

14. What is an aggregate table?

An aggregate table contains data you can calculate with functions like sum, average, maximum, etc.

15. What is OLTP?

Online transaction processing, or OLTP for short, provides 3-tier transaction-oriented applications. OLTP manages a company's or organization's daily operations.

16. Define check constraint.

A check constraint is employed to confirm a column's range of values.

Intermediate Data Modeling Interview Questions

17. What is the algorithm for sequence clustering?

The algorithm for sequence clustering gathers connected or similar paths and data sequences with events.

18. What are continuous and discrete data?

Discrete data is a specified or finite type of data. Continuous data changes continuously and in an organized way.

19. What is the time series algorithm?

A time series algorithm is a technique for predicting continuous values of data.

20. What do you understand about the bit-mapped index?

A bit-mapped index is a unique database index that employs bitmaps (bit arrays) to process bitwise operations and respond to queries.

21. What is data mining?

Data mining is a practice that analyzes huge data sets to find patterns and trends beyond simple analysis. Programmers use data mining to: 

  • Manage risk
  • Detect fraud
  • Strategize cybersecurity

22. What is a self-recursive relationship?

Recursive relationships are connections between a table's primary key and a separate column.

23. Describe relational data modeling

Relational data modeling is the representation of objects in normalized tabular forms.

24. What is predictive modeling analytics?

Predictive modeling analytics is a testing or validation process for a model used to forecast results. You can apply it to statistics, artificial intelligence, and machine learning.

25. What kinds of constraints are there?

Some kinds of constraints include unique, null values, foreign keys, composite keys, check constraints, and other variations.

26. What is a data-modeling tool?

A data modeling tool is a software program that helps you create data structures. These tools include Altova DatabaseSpy, Casewise, Case Studio 2, Borland Together, and others.

27. Describe hierarchical DBMS.

DBMS is a hierarchical database where data is arranged and stored in a tree-like pattern. Hierarchical structures are used to store data. Using a parent-child relationship, you can use DBMS to visualize data. Although a parent in a hierarchical DBMS may have numerous children, each child only has one parent.

28. What is a network model?

The network model has a hierarchical structure. It has numerous records because it permits more than one relationship to link the records. Using this model, you can create a set of parent records and child records. In addition, you can execute sophisticated table associations since each record can be a member of numerous sets.

29. What is hashing?

A method for searching every index value and obtaining necessary data is hashing. You can use this method to determine a data point’s precise disc location without using the structure of the index.

30. What are natural or business keys?

A business or natural key is a field specifically identifying an entity, such as a client ID, employee ID, email, etc.

31. What is a compound key?

A compound key is represented by many fields and used when 

32. What does DBMS's fourth normal form mean?

The fourth normal form only permits key dependencies on non-candidate values.

33. What is a database management system?

A program called a database management system, or DBMS, stores and retrieves user data. It consists of many programs that change the database.

34. What is normalization?

Normalization is a database design method that arranges tables to lessen data dependencies and redundancy. It breaks up large tables into smaller tables and uses relationships to connect them.

35. What benefits does data modeling offer?

Here are some benefits of data modeling:

  • Aids in internal and external corporate communication
  • Supports the ETL process' documentation of data mappings
  • Identifies appropriate data sources to fill the model

Advanced-Data Modeling Interview Questions for Experienced Professionals

36. What is XMLA?

Online Analytical Processing uses XMLA, an XML analysis, as the standard for obtaining data (OLAP).

37. Describe the garbage dimension

Garbage dimension aids with junk data storage. We use it when you can’t properly store data in a schema. 

38. Explain chained data replication.

Chained data replication refers to a situation where a secondary node chooses a destination using ping time or when the secondary node is nearest.

39. Explain virtual data warehousing.

Virtual data warehousing provides a perspective of the finished data as a whole, but doesn’t include historical data. Furthermore, virtual data warehousing is a logical data model containing metadata.

40. Describe a data warehouse snapshot.

A snapshot is an entire data visualization at the point where the data extraction process begins. 

41. What is a bi-directional extract?

A bi-directional extract is a system's capacity to extract, purify, and transport data in two directions.

Popular DBMS software includes:

  • MySQL
  • Microsoft Access
  • Oracle
  • PostgreSQL

43. List all the types of cardinal relationships.

Different types of key cardinal relationships include:

  • Many-to-One Relationships
  • Many-to-Many Relationships
  • One-to-One Relationships
  • One-to-Many Relationships

44. What is PDAP?

PDAP is a data cube that keeps information in summary form. It enables speedy data analysis and reporting for the user. 

45. What is forward data engineering?

Forward data engineering describes the automatic conversion of a logical model into a physical tool.

46. What is a data warehouse?

A data warehouse is an integrated, non-volatile, time-variant, subject-oriented database, made to deliver analysis instead of transactions (Inmon). Dan Lindstedt's Data Vault serves as the main model for it. This combination offers the best data warehousing architecture.

47. What is database cardinality?

In database terminology, "cardinality" typically refers to the frequency of values in data. 

48. What is a foreign key?

A foreign key references the row or a document in another collection of the table.

49. What conditions should be met for the 5th normal form?

A table cannot have any smaller tables in a lossless decomposition to be considered in fifth normal form.

50. What is RDBMS?

A relational database management system or RDBMS is a software system consisting of relational databases, which store data in tables. Both columns and rows are referred to as tuples. For instance, the Microsoft SQL server is an RDBMS.

Bonus Tips

Almost ready for your interview? Finish your prep with these helpful tips: 

Apart from this, you can follow some bonus tips to ace your data modeler interview: 

  • Apply your knowledge to practice so you’re prepared for scenario-based data modeling interview questions. 
  • Keep notes and record the most difficult dimensional modeling interview question. Study that question in greater detail. 
  • Mention all your intermediate-level and expert-level skills in your resume
  • Share your experience on related projects, even if it’s through course practice or Bootcamp assignments.
  • Conduct mock interviews with a friend, or practice reciting the answers to data modeling questions in the mirror. 

Conclusion

Review these data modeling interview questions every day for a week before your interview — we have a feeling you’ll ace it! And if you’re looking for more tips on scoring a career in data structuring?

Frequently Asked Questions

1. What Are the Three Types of Data Modeling?

Data modeling comes in three varieties: conceptual, logical, and physical.

2. What is Data Modeling in SQL?

Data modeling in SQL is the method of describing a complicated software system’s design through a simple visual, utilizing text and symbols to denote the data flow’s direction.

3. What are Examples of Data Modeling?

Examples include creating an ER diagram for a shopping app, library system, or hotel reservation system.

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Sameeksha Medewar

Sameeksha Medewar

Sameeksha is a freelance content writer for more than half and a year. She has a hunger to explore and learn new things. She possesses a bachelor's degree in Computer Science. View all posts by the Author

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