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You should never go into an interview unless you are completely prepared. And if you're preparing for a data modeling interview, 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.
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In this article, we’ll be covering:
For freshers, the following data modeling interview questions for data engineers need to be prepared:
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.
The primary benefits of data modeling are:
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:
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.
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.
When applying for intermediate-level roles, these are the data modeling interview questions for data engineers you can expect:
The most common errors that can occur during data modeling are:
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.
The dimensions used to coordinate the historical as well as current data in data warehousing are known as slowly changing dimensions. Its four types are — SCD Type 0 through SCD Type 3.
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.
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.
If you’re an experienced professional, do go over the following data modeling interview questions for data engineers:
The answer is no; it’s not a requirement. However, denormalized databases can be easily accessed, are easy to maintain, and are less redundant.
NoSQL databases have the following pros:
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.
When a dimension is confirmed, it is attached to a minimum of two fact tables.
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.
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 are looking to build a career in it, read Career Path to Become a Successful Data Scientist.
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 3 major components of a data model?
The 3 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?
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