ETL Tester
10+ ETL Tester Interview Questions and Answers for Freshers
Q1. 1. Fetch last record of the column. 2. Dense rank vs rank 3. Fetch end of 5 character from the string of the column
The interview questions are related to SQL and data manipulation.
To fetch the last record of a column, you can use the ORDER BY clause with DESC keyword and LIMIT 1.
Dense rank and rank are both ranking functions in SQL, but dense rank assigns consecutive rank numbers to rows, while rank leaves gaps in the ranking sequence.
To fetch the end of 5 characters from a string column, you can use the RIGHT function in SQL.
Q2. What type of data validation you performed.
I performed various types of data validation including format validation, completeness validation, and referential integrity validation.
Format validation: Ensuring that the data is in the correct format as per the defined specifications. For example, validating that a date field is in the format 'YYYY-MM-DD'.
Completeness validation: Checking if all the required fields are present and populated in the data. For example, ensuring that a customer record has a name, address, and ...read more
Q3. Difference between snowflake schema and star schema
Snowflake schema is a normalized form of star schema with additional dimension tables.
Snowflake schema is a data modeling technique used in data warehousing.
In snowflake schema, dimensions are normalized into multiple related tables.
Snowflake schema reduces redundancy and improves data integrity.
Star schema is a denormalized form of snowflake schema with a single dimension table.
In star schema, dimensions are not normalized and are directly linked to the fact table.
Star schem...read more
Q4. Expected CTC in present company
I prefer not to disclose my current salary as it is confidential.
It is not appropriate to disclose current salary as it is confidential information.
I am open to discussing a fair and competitive salary for the position.
My focus is on finding a challenging role that aligns with my skills and experience.
I am willing to negotiate based on the job responsibilities and market standards.
Q5. Flexible to work any environment
Yes
I am flexible to work in any environment, be it a team or individual work
I can adapt to different work cultures and work styles
I am open to learning new technologies and tools
I can work in different time zones and shifts if required
Q6. SQL query to find second Max salary.
Use SQL query with subquery to find second highest salary.
Use ORDER BY and LIMIT to get the second highest salary.
Use a subquery to exclude the highest salary from the result set.
Example: SELECT MAX(salary) FROM employees WHERE salary < (SELECT MAX(salary) FROM employees);
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Q7. What customer do with data.
Customers use data for various purposes such as analysis, decision-making, reporting, and personalization.
Data is used for analysis to gain insights and identify patterns or trends.
Data helps in decision-making by providing information and supporting evidence.
Data is used for reporting to communicate information and track performance.
Data enables personalization by tailoring products or services based on customer preferences.
Examples: analyzing sales data to identify top-sell...read more
Q8. Query to fetch 5th highest salary
Use SQL query with ORDER BY and LIMIT to fetch 5th highest salary.
Use ORDER BY clause to sort salaries in descending order
Use LIMIT 1 OFFSET 4 to fetch the 5th highest salary
ETL Tester Jobs
Q9. Ready to work any location
Yes, I am willing to work at any location.
I am open to relocation and willing to adapt to new environments.
I understand that the job may require me to travel or work at different locations.
I am excited about the opportunity to explore new places and meet new people.
I am committed to delivering quality work regardless of the location.
Q10. Difference between fact and dimension.
Fact tables contain quantitative data that can be measured, while dimension tables contain descriptive attributes related to the facts.
Fact tables store numerical data such as sales revenue, quantity sold, etc.
Dimension tables store descriptive attributes like product name, customer name, etc.
Fact tables are typically larger in size compared to dimension tables.
Fact tables are connected to dimension tables through foreign keys.
Q11. Common validation in etl testing
Common validation techniques in ETL testing include data completeness, data accuracy, data transformation, and data quality checks.
Data completeness validation ensures that all expected data is loaded into the target system.
Data accuracy validation involves verifying that the data is correctly transformed and loaded without any errors.
Data transformation validation checks if the data is transformed according to the business rules and requirements.
Data quality checks involve v...read more
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