Data Modeling Interview Questions and Answers
Freshers / Beginner level questions & answers
Ques 1. What is data modeling?
Data modeling is the process of creating a visual representation of the structure and relationships within a database. It helps in understanding and organizing data for efficient storage, retrieval, and management.
Example:
Example: Entity-Relationship Diagram (ERD) or UML Class Diagram.
Ques 2. Explain the concept of cardinality in data modeling.
Cardinality defines the relationship between two entities, indicating how many instances of one entity are related to a specific instance of another entity. It is expressed as 'one-to-one,' 'one-to-many,' or 'many-to-many.'
Example:
Example: In a 'Customer' and 'Order' relationship, cardinality may be 'one-to-many,' indicating a customer can place multiple orders.
Ques 3. What is a surrogate key?
A surrogate key is an artificial key assigned to uniquely identify each record in a table. It is typically a system-generated or sequentially assigned value and is used as the primary key.
Example:
Example: Using an auto-incremented integer as a surrogate key for a 'Product' table.
Ques 4. What is a foreign key?
A foreign key is a field that refers to the primary key in another table. It establishes a link between two tables, enforcing referential integrity and defining relationships.
Example:
Example: In a 'Order' table, a foreign key 'customer_id' refers to the primary key 'customer_id' in the 'Customer' table.
Ques 5. What is the difference between a primary key and a unique key?
Both primary keys and unique keys enforce uniqueness in a column, but a table can have only one primary key, whereas it can have multiple unique keys.
Example:
Example: In a 'Person' table, the 'SSN' column can be a primary key, ensuring each person has a unique social security number.
Ques 6. What is a data mart, and how does it differ from a data warehouse?
A data mart is a subset of a data warehouse that is focused on specific business functions or user groups. It is smaller in scope compared to a data warehouse, which covers the entire organization.
Example:
Example: Creating a data mart specifically for finance-related data within a larger enterprise data warehouse.
Ques 7. What is a composite key, and when would you use it?
A composite key is a key that consists of multiple columns to uniquely identify a record. It is used when a single column cannot guarantee uniqueness, but the combination of multiple columns does.
Example:
Example: Using a composite key of ('DepartmentID', 'EmployeeID') to uniquely identify employees within each department.
Ques 8. What is a data mart, and how does it differ from a data warehouse?
A data mart is a subset of a data warehouse that is focused on specific business functions or user groups. It is smaller in scope compared to a data warehouse, which covers the entire organization.
Example:
Example: Creating a data mart specifically for finance-related data within a larger enterprise data warehouse.
Ques 9. What is a composite key, and when would you use it?
A composite key is a key that consists of multiple columns to uniquely identify a record. It is used when a single column cannot guarantee uniqueness, but the combination of multiple columns does.
Example:
Example: Using a composite key of ('DepartmentID', 'EmployeeID') to uniquely identify employees within each department.
Ques 10. What is a fact table, and how is it different from a dimension table?
A fact table contains quantitative data, such as sales or revenue, and is surrounded by dimension tables that provide context to the data. Dimension tables describe the who, what, where, when aspects of the facts.
Example:
Example: In a retail data warehouse, a 'Sales' fact table might include 'ProductID,' 'CustomerID,' 'DateID,' and 'SalesAmount.'
Ques 11. Explain the concept of database normalization.
Database normalization is the process of organizing data to minimize redundancy and dependency by dividing tables into smaller, related tables. Normal forms (1NF, 2NF, 3NF, BCNF) guide this process.
Example:
Example: Breaking down a 'Customer' table into 'Customer' and 'Address' tables to eliminate duplicate address information.
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