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ETL is ordinarily connected with Data Warehousing ventures however there in actuality any type of bulk data development from a source to an objective can be viewed as ETL. Large organizations regularly have a need to move application data starting with one source then onto the next for data migration or data integration purposes.
ETL testing can be categorized into four different sub categories irrespective of technology or ETL tools used in it. The four categories are listed below in detailed.
New Data Warehouse Testing : New DW is built and verified from scratch. Data input is taken from customer requirements and different data sources and new data warehouse is build and verified with the help of ETL tools.
Migration Testing : In this type of project customer will have an existing DW and ETL performing the job but they are looking to bag new tool in order to improve efficiency.
Change Request : In this type of project new data is added from different sources to an existing DW. Also, there might be a condition where customer needs to change their existing business rule or they might integrate the new rule.
Report Testing : Report are the end result of any Data Warehouse and the basic propose for which DW is build. Report must be tested by validating layout, data in the report and calculation.
ETL stands for extract tranform load. it is a process of how data is loaded from source system to data warehousing.
ETL testing is very interesting and informative among the software testing tools. ETL is a process to testing how the data is loaded into the data ware house. It is the initial feature to start a project because reporters or developers retrieve information from data ware house to perform work.
As per quality assurance services ETL is the process which is used during transferring of data between databases.
ETL testing is used for the confirmation whether or not the data transformation working smoothly. Verifying that the data maintains its integrity and accuracy once its transformed, loaded and extracted from the source to the data warehouse. Aim of ETL testing is to maintain a high level of confidence among end-users in the data stored in the data warehouse.
Below are the different types of ETL testing:
Data Validation Testing
I will share my thoughts.
ETL stands for Extract-Transform-Load and it is a process of how data is loaded from the source system to the data warehouse. Data is extracted from an OLTP database, transformed to match the data warehouse schema and loaded into the data warehouse database.
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ETL stands for Extract-Transform-Load and it is a process of how data is loaded from the source system to the data warehouse. Data is extracted from an OLTP database, transformed to match the data warehouse schema and loaded into the data warehouse database
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As per my understanding with quality assurance services,
ETL stands for Extract Transform and Load. It Deals with how the data is loaded in Warehouses and then transformed into meaningful form and then it is again loaded into Data Warehouses.
Testing on ETL is done to ensure that:
1. Data from systems are extracted correctly.
2. Data is transformed in expected form.
3. Transformed data is loaded in Destination system correctly.
Types of ETL testing
1. Validation Testing
- This deals with mapping the data in Destination system with source system.
2. Meta Data testing
In This type of testing we check Data indexes, Data Constraints,Lengths.
3. Data Accuracy testing
This testing is done to verify that data is correctly extracted and transformed.
4. Data Transform Testing
This type of testing is done to ensure that types of data is in expected format or not.