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ETL Testing Interview Questions And Answers:

Q 1  What exactly do you mean by ETL?
ETL stands for Extract Transform Load and is widely regarded as one of the essential tools in the data warehousing architecture. Its main task is to handle data management for the business process which is complex and is useful for the business in many ways.

Q2  What is partitioning in ETL?
The transactions are needed to be divided for better performance. The same processes are known as subdividing. It simply makes sure that the server can access the sources through multiple connections.

Q3  what is the factless fact table in ETL?
ETL Tester is defined as the table without measures in the ETL. There are a number of occasions that can be managed directly with the same. It can also record events that are connected to the employees or with the management and this task can be accomplished in a very reliable manner.

Q4  How you will make use of the Lookup in ETL Transformation?
It is one of the perfect in fact, one of the very useful approaches in the ETL. In addition to this, it simply makes sure of boosting the performance of a dimension that is changing at a very slow rate. It makes sure that the users can get a related value from a table.

Q5  What are commercial ETL tools?
Commercial ETL tools are:
1-Adeptia ETL.
3-Business Objects Data Services.
4-Informatica Power Center.
5-Business Objects Data Integrator (BODI) Confluent.

Q6  What does ETL stand for?
ETL stands for Extract, Transform, and Load, these database functions are combined into one tool to take data out of one database and place it into another database. This extract process is the process of reading data from a database.

Q7   What is Cube in ETL Testing?
ETL. Cubes are data processing units composed of fact tables and dimensions from the data warehouse. They provided a multidimensional analysis.

Q8  What is the ETL example?
The very example of ETL is ETL is used in Data warehousing. The user needs to fetch the historical data as well as current data for developing the data warehouse. The ETL definition suggests. This process needs to be used in data warehousing.

Q9  Why do we need a staging area in an ETL process?
A staging area is an intermediate area that sits between data sources and data warehouse data marts systems and staging areas can be created to provide many benefits and the motivations for their use are to increase the efficiency of ETL processes, ensure and data integrity, and support data quality operations.

Q10  what do you understand by ETL Testing?
ETL Testing is complete before data is moved into a production Data Warehouse system. The main objective of ETL testing is to identify data defects and general errors that occur prior to the processing of data for the analytical scribe. It is also called Table Balancing or production reconciliation.

Q11  What are the different ETL Testing categories as per their function?
ETL testing can be divided into the following categories based on their functions
1=Source to Target Count Testing involves the matching of the count of records in the source and target system.
2=Source to Target Data Testing involves and data validation between source and target system.
3=Data Transformation Testing confirms the mapping of objects in the source and target system. And involves checking the functionality of data in the target system.
4=System Integration Testing involves testing all the individual systems, and later combine the result to find if there is any deviation.

Q12  What are your responsibilities as an ETL Tester?
These are the responsibilities of an ETL tester.
-Verifying the tables in the source system.
-In the ETL process applying the transformation logic before loading the data.
-The data loading from the Staging area to the target system.

Q13  What are the common ETL Testing scenarios?
These are the most common ETL testing scenarios:

1-Structure validation.
2-Validating Mapping document.
3-Validate Constraints.
4-Data Consistency check.
5-Data Completeness Validation
6-Data Correctness Validation.
7-Data Transform validation.
8-Data Quality Validation.
9-Null Validation.
10-Duplicate Validation etc.

Q14  What are the tracing level in ETL testing and its types?
The tracing levels define the volume of data stored in the log files. They are divided into two categories, these are Normal and Verbose. The normal category defines the tracing level in detail while the verbose categories define the tracing level at each row.

Q15  Name a few popular ETL bugs?
The popular ETL bugs are:
-Source bugs.
-Calculation bugs.
-ECP-related bugs.
-Load condition bugs
-User-Interface bugs.

Q16  How will you define the Staging place in ETL testing?
The staging place is not a permanent storage area that is used during the Data Integration process. Here, Data is analyzed carefully for redundancy.

Q17  Explain the major ETL testing operations in detail?
ETL tools verify either data is fetched perfectly or not. And it verifies either data is converted or loaded correctly at a perfect time as needed by the business requirements to enhance the overall scalability and perfect performance.

Q18  Define Facts in ETL testing and different types of Facts?
These facts are the dimensions that are used to analyze data on different parameters. The three popular facts in ETL testing include.

Q19  What is the difference between Manual Testing and ETL Testing?
1. The difference between manual testing and ETL testing. Manual testing is related to the functionality of the program and ETL testing is related to the databases and their count.

2. ETL is the automated testing process and where you don’t need any technical knowledge other than the software. Also, ETL testing is extremely higher and systematic and assure top results as needed by the businesses.

3. manual testing is highly time-consuming. So where you need technical knowledge to write the test cases and the scripts. And it is slow, needs effort, and highly prone to errors.

Q20  Where users can use ETL concepts. Give some examples? Before the ETL tool user needs to write long code for data transformation to data loading ETL makes life simple.
There are the following examples where we are using the ETL.
1-Data warehousing.
2-Data Migrations.
3-Mergers and Acquisitions.

Q21  Explain how ETL is used in third-party data management?
The big organizations always give different application development to different kinds of vendors. This means not a single vendor is managing everything. For example. Where billing is managed by one company and is managed by another company. If a company needs some data from the company that is managing the Billing. That company will receive a data feed from the other company. To load the data from the feed ETL process is used.

Q22  ETL is used in Data warehousing?
The most common example of ET it’s used in data warehousing. Extract, Transform, and loading of the data. This process needs to be used in data warehousing highly. A simple example of this is managing sales data in a shopping mall. If the user wants the previous data, as well as current data in the shopping mall first step, is always the user needs to follow the ETL process. Then that data will be used for reporting purposes.

Q23  How ETL is used in Data migration projects?
ETL tools are used in data migration projects. If the organization is managing the data in oracle (10 G) previously and now the organization wants to go for a server cloud database then there is a need to migrate the data from source to target. To do it kind of migration the ETL tools are very useful.

Q24  Explain Data extraction (ETL) types?
There are 2 types of Data Extraction:
1. Full Extraction: All the data from source systems or operational systems gets extracted into the staging area.2. Partial Extraction: In sometimes we get notification from the source system to update a specific date. It is called Delta load.

Q25  Explain data transformation in ETL?
Data Extracted from the source system is into raw format. We need to transform it before loading it into the target server.
There are the following steps in transformation:
1. Selection: Select data to load in the target.
2. Matching: Match the data with the target system.
3. Data Transforming: We need to change data as per target table structures.

Q26  Compare ETL Testing with Manual Testing?
The criteria ETL Testing Manual Testing is a basic process of writing scripts in automating the testing procedure. the method of observing and testing requirements no need for additional technical knowledge other than the understanding of the software needs technical knowledge of shell scripting efficiency fast and systematic and provides top results Needs time.

Q27  When we need the staging area in the ETL process?
The staging area is a central area that is available between the data sources and data warehouse/data marts systems.
The staging area is designed to provide many benefits, but the primary goal is to use the staging area. It is used to increase efficiency, ensure data integrity, and support data quality operations.

Q28  What is the responsibility of the ETL tester?
The responsibility of ETL Tester is divided into three major categories:
1-Stage Tables.
2-Business Logic Transformation.
3-Target table loading from the staging table, once we apply the transformation.
4-Responsibilities of ETL tester are:
5-ETL tester tests the ETL software thoroughly.
6-The tester will check all test components of the ETL Data Warehouse.
7-The tester will execute the data-driven in the backend.
8-The tester creates the design and executes the test cases, test plans or test harness, etc.

Q29  What are the steps followed in the ETL testing process?
These steps are followed in the ETL Testing process.
Step 1 Requirement Analyzing.
Step 2. Validation and Test Estimation.
Step 3. Test Planning and designing the testing environment.
Step 4. Test Data Preparation and Execution.
Step 5. Summary Report.

Q30  What are the Key benefits of ETL Testing?
Key benefits of ETL Testing.
1-Data Security.
2-Data Accuracy.
3-Reporting efficiency.

Q31  What are the ETL tools available in the market?
The popular ETL tools available in the market are:
1- IBM- Web sphere Data Stage.
2- Informatics- Power Center.
3- SAP- Business objects data service.
4- SAS – Data Integration Studio.
5- Oracle- Warehouse Builder.
6-Open source Clover ETL.

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