Top 25 ETL Developer Interview Questions with Answers tailored for experienced professionals. These questions and answers are designed to be clear, concise, and easy to understand, helping you prepare effectively for your interview:
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1. What is ETL?
Answer:
ETL stands for Extract, Transform, Load. It is a process used in data integration:
- Extract: Data is collected from various sources (e.g., databases, APIs, files).
- Transform: Data is cleaned, filtered, and formatted to meet business requirements.
- Load: The transformed data is loaded into a target database or data warehouse for analysis.
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2. What are the key differences between ETL and ELT?
Answer:
- ETL: Data is transformed before loading into the target system. Best for structured data and smaller datasets.
- ELT: Data is loaded into the target system first, and transformations happen there. Ideal for big data and cloud-based systems.
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3. What are the most common tools used in ETL?
Answer:
Popular ETL tools include:
- Informatica PowerCenter
- Talend
- Microsoft SSIS (SQL Server Integration Services)
- Apache NiFi
- AWS Glue
- Oracle Data Integrator (ODI)
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4. What is a staging area in ETL?
Answer:
A staging area is a temporary storage area where raw data is held before transformation. It helps in:
- Data validation
- Reducing load on source systems
- Simplifying error handling
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5. What is a surrogate key, and why is it used?
Answer:
A surrogate key is a unique identifier (e.g., an auto-incremented number) added to a table in a data warehouse. It is used to:
- Replace natural keys (which may change over time).
- Improve query performance.
- Simplify joins between tables.
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6. What is the difference between incremental load and full load?
Answer:
- Full Load: All data is extracted and loaded into the target system, replacing existing data.
- Incremental Load: Only new or updated data since the last load is extracted and loaded, saving time and resources.
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7. How do you handle NULL values in ETL?
Answer:
NULL values can be handled by:
- Replacing them with default values (e.g., 0, "N/A").
- Filtering them out if not required.
- Using conditional logic to handle them during transformation.
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8. What is a lookup transformation in ETL?
Answer:
A lookup transformation is used to compare source data with reference data (e.g., a lookup table) to retrieve additional information or validate data.
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9. What is data cleansing, and why is it important?
Answer:
Data cleansing involves identifying and correcting errors, inconsistencies, and duplicates in data. It is important because:
- Ensures data accuracy.
- Improves decision-making.
- Enhances data quality in the target system.
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10. What is a slowly changing dimension (SCD)?
Answer:
SCD is a technique to manage changes in dimension tables over time. Common types include:
- Type 1: Overwrite old data with new data.
- Type 2: Add a new row for changes, preserving history.
- Type 3: Add a new column to track changes.
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11. What is the difference between a data warehouse and a database?
Answer:
- Database: Used for transactional processing (OLTP).
- Data Warehouse: Used for analytical processing (OLAP) and stores historical data from multiple sources.
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12. What is a fact table and a dimension table?
Answer:
- Fact Table: Contains measurable data (e.g., sales, revenue) and foreign keys to dimension tables.
- Dimension Table: Contains descriptive data (e.g., product, customer) used for filtering and grouping.
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13. What is CDC (Change Data Capture)?
Answer:
CDC is a technique to identify and capture changes in source data (e.g., new, updated, or deleted records) and apply them to the target system.
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14. What is the role of a metadata repository in ETL?
Answer:
A metadata repository stores information about ETL processes, such as data sources, transformations, and mappings. It helps in:
- Tracking data lineage.
- Debugging ETL processes.
- Improving documentation.
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15. How do you optimize ETL performance?
Answer:
- Use incremental loads instead of full loads.
- Parallel processing for large datasets.
- Optimize SQL queries and indexing.
- Use partitioning and clustering in the target system.
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16. What is a data mart?
Answer:
A data mart is a subset of a data warehouse, focused on a specific business function (e.g., sales, finance). It is smaller and more specialized.
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17. What is the difference between OLTP and OLAP?
Answer:
- OLTP (Online Transaction Processing): Handles real-time transactional operations (e.g., inserting, updating records).
- OLAP (Online Analytical Processing): Used for complex queries and data analysis.
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18. What is a star schema?
Answer:
A star schema is a data warehouse design with a central fact table connected to multiple dimension tables, resembling a star. It simplifies queries and improves performance.
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19. What is a snowflake schema?
Answer:
A snowflake schema is a normalized version of a star schema, where dimension tables are further broken down into sub-dimensions. It reduces redundancy but can be more complex.
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20. How do you handle errors in ETL processes?
Answer:
- Use error logging to capture failed records.
- Implement retry mechanisms for transient errors.
- Notify stakeholders for critical failures.
- Use data validation checks to prevent errors.
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21. What is the difference between a primary key and a foreign key?
Answer:
- Primary Key: Uniquely identifies a record in a table.
- Foreign Key: Links a record in one table to a primary key in another table.
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22. What is data profiling?
Answer:
Data profiling is the process of analyzing source data to understand its structure, quality, and relationships. It helps in designing effective ETL processes.
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23. What is the role of a scheduler in ETL?
Answer:
A scheduler automates the execution of ETL jobs at specified times or intervals, ensuring data is updated regularly without manual intervention.
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24. What is a data pipeline?
Answer:
A data pipeline is a set of processes that move data from source to destination, often involving ETL, data transformation, and loading.
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25. How do you ensure data security in ETL?
Answer:
- Encrypt sensitive data during transfer and storage.
- Use role-based access control (RBAC).
- Audit ETL processes regularly.
- Mask or anonymize sensitive data.
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These questions and answers cover the most critical aspects of ETL development and are designed to help you confidently tackle your interview.
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