Explore Courses
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Birla Institute of Management Technology Birla Institute of Management Technology Post Graduate Diploma in Management (BIMTECH)
  • 24 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Popular
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science & AI (Executive)
  • 12 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
University of MarylandIIIT BangalorePost Graduate Certificate in Data Science & AI (Executive)
  • 8-8.5 Months
upGradupGradData Science Bootcamp with AI
  • 6 months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
OP Jindal Global UniversityOP Jindal Global UniversityMaster of Design in User Experience Design
  • 12 Months
Popular
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Rushford, GenevaRushford Business SchoolDBA Doctorate in Technology (Computer Science)
  • 36 Months
IIIT BangaloreIIIT BangaloreCloud Computing and DevOps Program (Executive)
  • 8 Months
New
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Popular
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
Golden Gate University Golden Gate University Doctor of Business Administration in Digital Leadership
  • 36 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
Popular
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
Bestseller
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
IIIT BangaloreIIIT BangalorePost Graduate Certificate in Machine Learning & Deep Learning (Executive)
  • 8 Months
Bestseller
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in AI and Emerging Technologies (Blended Learning Program)
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
ESGCI, ParisESGCI, ParisDoctorate of Business Administration (DBA) from ESGCI, Paris
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration From Golden Gate University, San Francisco
  • 36 Months
Rushford Business SchoolRushford Business SchoolDoctor of Business Administration from Rushford Business School, Switzerland)
  • 36 Months
Edgewood CollegeEdgewood CollegeDoctorate of Business Administration from Edgewood College
  • 24 Months
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with Concentration in Generative AI
  • 36 Months
Golden Gate University Golden Gate University DBA in Digital Leadership from Golden Gate University, San Francisco
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Deakin Business School and Institute of Management Technology, GhaziabadDeakin Business School and IMT, GhaziabadMBA (Master of Business Administration)
  • 12 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science (Executive)
  • 12 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityO.P.Jindal Global University
  • 12 Months
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (AI/ML)
  • 36 Months
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDBA Specialisation in AI & ML
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
New
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGrad KnowledgeHutupGrad KnowledgeHutAzure Administrator Certification (AZ-104)
  • 24 Hours
KnowledgeHut upGradKnowledgeHut upGradAWS Cloud Practioner Essentials Certification
  • 1 Week
KnowledgeHut upGradKnowledgeHut upGradAzure Data Engineering Training (DP-203)
  • 1 Week
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
Loyola Institute of Business Administration (LIBA)Loyola Institute of Business Administration (LIBA)Executive PG Programme in Human Resource Management
  • 11 Months
Popular
Goa Institute of ManagementGoa Institute of ManagementExecutive PG Program in Healthcare Management
  • 11 Months
IMT GhaziabadIMT GhaziabadAdvanced General Management Program
  • 11 Months
Golden Gate UniversityGolden Gate UniversityProfessional Certificate in Global Business Management
  • 6-8 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
IU, GermanyIU, GermanyMaster of Business Administration (90 ECTS)
  • 18 Months
Bestseller
IU, GermanyIU, GermanyMaster in International Management (120 ECTS)
  • 24 Months
Popular
IU, GermanyIU, GermanyB.Sc. Computer Science (180 ECTS)
  • 36 Months
Clark UniversityClark UniversityMaster of Business Administration
  • 23 Months
New
Golden Gate UniversityGolden Gate UniversityMaster of Business Administration
  • 20 Months
Clark University, USClark University, USMS in Project Management
  • 20 Months
New
Edgewood CollegeEdgewood CollegeMaster of Business Administration
  • 23 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
KnowledgeHut upGradKnowledgeHut upGradBackend Development Bootcamp
  • Self-Paced
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 5 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
upGradupGradUI/UX Bootcamp
  • 3 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
upGradupGradDigital Marketing Accelerator Program
  • 05 Months

Top 20 Most Popular Data Modelling Interview Questions & Answers [For Beginners & Experienced]

Updated on 25 November, 2022

7.02K+ views
10 min read

Data Science is one of the most lucrative career fields in the present job market. And as competition picks up, job interviews are also getting more innovative by the day. Employers want to test candidates’ conceptual knowledge and practical understanding of relevant subjects and technology tools. In this blog, we will discuss some relevant data modelling interview questions to help you make a powerful first impression! 

Top Data Modelling Interview Questions and Answers

Here are 20 data modelling interview questions along with the sample answers that will take you through the beginner, intermediate, and advanced levels of the topic.

1. What is Data Modeling? List the types of data models.

Data modelling involves creating a representation (or model) of the data available and storing it in a database. 

A data model comprises entities (such as customers, products, manufacturers, and sellers) that give rise to objects and attributes that users want to track. For instance, a Customer Name is an attribute of the Customer entity. These details further take the shape of a table in a database.

There are three basic types of data models, namely:

  • Conceptual: Data architects and business stakeholders create this model to organise, scope, and define business concepts. It dictates what a system should contain.
  • Logical: Put together by data architects and business analysts, this model maps the technical rules and data structures, thus determining the system’s implementation regardless of a database management system or DBMS. 
  • Physical: Database architects and developers create this model to describe how the system should operate with a specific DBMS.

2. What is a Table? Explain Fact and Fact Table.

A table holds data in rows (horizontal alignments) and columns (vertical alignments). Rows are also known as records or tuples, whereas columns may be referred to as fields. 

A fact is quantitative data like “net sales” or “amount due”. A fact table stores numerical data as well as some attributes from dimensional tables. 

Check out our data science online courses to upskill yourself

3. What do you mean by (i) dimension (ii) granularity (iv) data sparsity (v) hashing (v) database management system?

(i) Dimensions represent qualitative data such as class and product. Therefore, a dimensional table containing product data will have attributes like the product category, product name, etc. 

(ii) Granularity refers to the level of information stored in a table. It can be high or low, with the tables containing transaction-level data and fact tables, respectively. 

(iii) Data sparsity means the number of empty cells in a database. In other words, it states how much data we have for a particular entity or dimension in the data model. Insufficient information leads to large databases as more space is required to save the aggregations. 

(iv) The hashing technique helps search index values for retrieving desired data. It is used to calculate the direct location of data records with the help of index structures.

(v) A Database Management System (DBMS) is software comprising a group of programs for manipulating the database. Its primary purpose is to store and retrieve user data. 

4. Define Normalisation. What is its purpose?

The normalisation technique divides larger tables into smaller ones, linking them using different relationships. It organises tables in a way that minimises the dependency and redundancy of the data. 

There can be five types of normalisations, namely:

  • First normal form
  • Second normal form
  • Third normal form
  • Boyce-Codd fourth normal form
  • Fifth normal form

5. What is the utility of denormalisation in data modelling?

Denormalisation is used to construct a data warehouse, especially in situations having extensive involvement of tables. This strategy is used on a previously normalised database. 

6. Elucidate the differences between primary key, composite primary key, foreign key, and surrogate key. 

A primary key is a mainstay in every data table. It denotes a column or a group of columns and lets you identify a table’s rows. The primary key value cannot be null. When more than one column is applied as a part of the primary key, it is known as a composite primary key.

On the other hand, a foreign key is a group of attributes that allows you to link parent and child tables. The foreign key value in the child table is referenced as the primary key value in the parent table. 

A surrogate key is used to identify each record in those situations where the users do not have a natural primary key. This artificial key is typically represented as an integer and does not lend any meaning to the data contained in the table. 

7. Compare the OLTP system with the OLAP process. 

OLTP is an online transactional system that relies on traditional databases to perform real-time business operations. The OLTP database has normalised tables, and the response time is usually within milliseconds. 

Conversely, OLAP is an online process meant for data analysis and retrieval. It is designed for analysing large volumes of business measures by category and attributes. Unlike OLTP, OLAP uses a data warehouse, non-normalised tables and operates with a response time of seconds to minutes. 

8. List the standard database schema designs.

A schema is a diagram or illustration of data relationships and structures. There are two schema designs in data modelling, namely star schema and snowflake schema.

  • A star schema comprises a central fact table and several dimension tables that are connected to it. The primary key of the dimension tables is a foreign key in the fact table.
  • A snowflake schema has the same fact table as the star schema but at a higher level of normalisation. The dimension tables are normalised or have multiple layers, which resembles a snowflake.

9. Explain discrete and continuous data. 

Discrete data finite and defined, such as gender, telephone numbers, etc. On the other hand, continuous data changes in an ordered manner; for example, age, temperature, etc.

10. What are sequence clustering and time series algorithms?

A sequence clustering algorithm collects:

  • Sequences of data having events, and
  • Related or similar paths. 

Time series algorithms predict continuous values in data tables. For instance, it can forecast the sales and profit figures based on employee performance over time. 

Now that you have brushed up your basics, here are ten more frequently asked data modelling questions for your practice! 

11. Describe the process of data warehousing. 

Data warehousing connects and manages raw data from heterogeneous sources. This data collection and analysis process allows business enterprises to get meaningful insights from varied locations in one place, which forms the core of Business Intelligence

12. What are the key differences between a data mart and a data warehouse?

A data mart enables tactical decisions for business growth by focusing on a single business area and following a bottom-up model. On the other hand, a data warehouse facilitates strategic decision-making by emphasising multiple areas and data sources and adopting a top-down approach.

13. Mention the types of critical relationships found in data models.

Critical relationships can be categorised into:

  • Identifying: Connects parent and child tables with a thick line. The child table’s reference column is a part of the primary key.
  • Non-identifying: The tables are connected by a dotted line, signifying that the child table’s reference column is not a part of the primary key.
  • Sef-recursive: A standalone column of the table is connected to the primary key in a recursive relationship. 

14. What are some common errors that you encounter while modelling data?

It can get tricky to build broad data models. The chances of failure also increase when tables run higher than 200. It is also critical for the data modeller to have adequate workable knowledge of the business mission. Otherwise, the data models run the risk of going haywire.

Unnecessary surrogate keys pose another problem. They must not be used sparingly, but only when natural keys cannot fulfil the primary key’s role. 

One can also encounter situations of inappropriate denormalisation where maintaining data redundancy can become a considerable challenge. 

15. Discuss hierarchical DBMS. What are the drawbacks of this data model?

A hierarchical DBMS stores data in tree-like structures. The format uses the parent-child relationship where a parent may have many children, but a child can only have one parent. 

The drawbacks of this model include:

  • Lack of flexibility and adaptability to changing business needs;
  • Issues in inter-departmental, inter-agency, and vertical communications;
  • Problems of disunity in data. 

16. Detail two types of data modelling techniques.

Entity-Relationship (E-R) and Unified Modeling Language (UML) are the two standard data modelling techniques.

E-R is used in software engineering to produce data models or diagrams of information systems. UML is a general-purpose language for database development and modelling that helps visualise the system design.

upGrad’s Exclusive Data Science Webinar for you –

Watch our Webinar on The Future of Consumer Data in an Open Data Economy

17. What is a junk dimension?

A junk dimension is born by combining low-cardinality attributes (indicators, booleans, or flag values) into one dimension. These values are removed from other tables and then grouped or ”junked” into an abstract dimension table, which is a method of initiating ‘Rapidly Changing Dimensions’ within data warehouses. 

18. State some popular DBMS software.

MySQL, Oracle, Microsoft Access, dBase, SQLite, PostgreSQL, IBM DB2, and Microsoft SQL Server are some of the most-used DBMS tools in the modern-day software development arena. 

19. What are the advantages and disadvantages of using data modelling?

Pros of using data mining:

  • Business data can be better managed by normalising and defining attributes.
  • Data mining allows the integration of data across systems and reduces redundancy.
  • It makes way for an efficient database design.
  • It enables inter-departmental cooperation and teamwork.
  • It allows easy access to data.  

Cons of using data modelling:

  • Data modelling can sometimes make the system more complex. 
  • It has a limited structural dependency.

20. Explain data mining and predictive modelling analytics.

Data mining is a multi-disciplinary skill. It involves applying knowledge from fields like Artificial Intelligence (AI), Machine Learning (ML), and Database Technologies. Here, practitioners are concerned with uncovering the mysteries of data and discovering previously unknown relationships. 

Predictive modelling refers to testing and validating models that can predict specific outcomes. This process has several applications in AI, ML, and Statistics. 

Career Insights for Aspiring Data Modelers 

Whether you are looking for a fresh job, promotion, or career transition, upskilling in a relevant discipline can considerably improve your hiring chances.

You should consider checking out IIIT-B & upGrad’s Executive PG Programme in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

With this, we wind up this discussion on data modelling jobs and interviews. We are certain that the data mentioned above modelling interview questions and answers will help you clarify your problem areas and perform better in the placement process!

Frequently Asked Questions (FAQs)

1. How much does a Data Modeler make a year?

There are plenty of factors that would really affect the salary of any individual in the field of data modeling. On average, the salary of a data modeler is Rs. 12,00,000 per annum. It would depend a lot on the company that you are working with. Even if you are starting out as a data modeler, the lowest package is Rs. 600,000 per annum, while the highest package one can expect up to Rs. 20,00,000 per annum.

2. Is it difficult to crack a Data Modeling interview?

Data modeling is an emerging field with a huge demand in the market. On the other hand, the number of professionals who are proficient in data modeling is pretty less. The interview might seem a bit difficult if you haven’t prepared properly, but you can expect a decent interview with proper preparation.
Along with clearing the fundamentals of data modeling, you should also prefer going through some of the most frequently asked interview questions. This will make it much easier for you to answer the questions being asked in the interview as you already have an idea about the different questions being asked as well as the way of answering them.

3. What skills do I need to have to be a Data Modeler?

The skills required for becoming a data modeler are quite different from the ones needed for getting into systems administration or programming. Usually, these types of jobs demand technical skills, but the case is different over here. One needs to be well-versed on the logical side for becoming a data modeler. Some of the key skills that one needs to develop are:
1. Conceptual Design
2. Internal Communication
3. User Communication
4. Abstract Thinking
Even if you are not very proficient on the technical side, you can get a job as a data modeler if you can think abstractly and conceptually.