If you are a fresher or a professional and looking for a platform to prepare for job interviews in ETL Testing, then this is the right place for you. The ETL Testing Interview Questions blog is designed by experts to assist you in moving ahead in your ETL Testing career without any difficulty. It guides you through the basic-to-advanced level questions that are generally asked during job interviews in this field. Go through the ETL interview questions listed below and make sure to prepare them before going for your job interview:
Q1. Compare ETL Testing with Manual Testing.
Q2. What is ETL?
Q3. Why ETL Testing is required?
Q4. What are the responsibilities of an ETL Tester?
Q5. What are the various tools used in ETL?
Q6. Define ETL Processing.
Q7. What do ETL Testing operations include?
Q8. List a few ETL bugs.
Q9. What is Fact? What are the types of Facts?
Q10. What are Cubes and OLAP Cubes?
The two parts of this ETL Testing Interview Questions blog are as follows:
Check out this video on ETL Testing Tutorial:
Basic Interview Questions
1. Compare ETL Testing with Manual Testing.
||Writing scripts for automating the testing process
||A method of observing and testing
||No need for additional technical knowledge other than the understanding of the software
||Needs technical knowledge of SQL and Shell scripting
||Fast and systematic, and provides top results
||Needs time and effort, and is prone to errors
2. What is ETL?
ETL refers to the Extracting, Transforming, and Loading of data from any outside system to the required place. These are the basic three steps in the data integration process.
‘Extracting’ means locating data and removing it from the source file; ‘Transforming’ is the process of transporting it to the required target file, and in the ‘Loading’ stage the file is loaded to the target system in the specified format.
3. Why ETL Testing is required?
- To keep an eye on data that is being transferred from one system to another
- To keep track of the efficiency and speed of the process
- To achieve fast and the best results
Learn more about the ETL Testing process through this Data Warehouse Tutorial!
4. What are the responsibilities of an ETL Tester?
An ETL Tester:
- Requires in-depth knowledge of the ETL tools and processes
- Needs to write SQL queries for various scenarios during the testing phase
- Should be able to carry out different types of tests and keep a check on the other functionalities of the process
- Needs to carry out quality checks on a regular basis
5. What are the various tools used in ETL?
- Cognos Decision Stream
- Oracle Warehouse Builder
- Business Objects XI
- SAS Business Warehouse
- SAS Enterprise ETL Server
Intermediate Interview Questions
6. Define ETL Processing.
ETL Testing Process:
Although there are many ETL tools, there is a simple testing process commonly used in ETL Testing. It is as important as the implementation of the ETL tool into your business. Having a well-defined ETL Testing strategy can make the testing process much easier. Hence, this process needs to be completed before you start the data integration with the selected ETL tool.
In this ETL Testing process, a group of experts comprising the programming and developing team will start writing SQL statements. The development team may customize them according to the requirements.
ETL Testing process has the following stages:
- Analyzing requirements: Understanding the business structure and their particular requirements.
- Validation and test estimation: Estimating the time and expertise required to carry on with the procedure.
- Test planning and designing the testing environment: Based on the inputs from the estimation, an ETL environment is planned and worked out.
- Test data preparation and execution: Data for the test is prepared and executed as per the requirements.
- Summary report: Upon the completion of the test run, a brief summary report is prepared for improvising and concluding.
To learn more in detail, enroll in Intellipaat’s ETL Testing Course!
7. What do ETL Testing operations include?
ETL Testing includes:
- Verifying whether the data is transformed accurately according to business requirements
- Verifying that the projected data is loaded into the data warehouse without any truncation or data loss
- Making sure that the ETL application reports any invalid data and replaces with default values
- Making sure that the data loads within the expected time frame to improve scalability and performance
8. List a few ETL bugs.
- Calculation Bug
- User Interface Bug
- Source Bug
- Load Condition Bug
- ECP-related Bug
In addition to the above ETL Testing questions, there may be other vital questions where you might be asked to mention the ETL tools that you have used earlier. Also, you might be asked about any debugging issues you have faced in your earlier real-time experience. Interested in learning ETL in detail? Check out our ETL Tutorial for Beginners!
9. What is Fact? What are the types of Facts?
Fact is a central component of a multi-dimensional model that contains the measures to be analyzed. Facts are related to dimensions.
Types of facts are:
- Additive Facts
- Semi-additive Facts
- Non-additive Facts
If you have any queries, visit our ETL Testing Community and clarify all your doubts today!
10. What are Cubes and OLAP Cubes?
Cubes are data processing units comprised of fact tables and dimensions from the data warehouse. They provide a multi-dimensional analysis.
OLAP stands for ‘Online Analytics Processing,’ and OLAP Cubes store voluminous data in a multi-dimensional form for reporting purposes. They consist of facts called ‘measures’ categorized by dimensions.
11. Mention the types of Data Warehouse applications. What is the difference between Data Mining and Data Warehousing?
Types of data warehouse applications are:
- Info Processing
- Analytical Processing
- Data Mining
Data mining can be defined as the process of extracting hidden predictive information from large databases and interpreting the data, while data warehousing may make use of a data mine for the analytical processing of the data in a faster way. Data warehousing is the process of aggregating data from multiple sources into one common repository.