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Post By Admin Last Updated At 2020-09-29
How to execute Informatica ETL testing and its benefits

ETL or Extract, Transform and Load is a process that gathers data from source systems, transforms the data into meaningful information, then loads the data into a data warehouse. ETL testing refers to the process of validating, verifying, and authorizing data by preventing data duplication and loss. ETL testing is one of the important aspects of any Business Intelligence or BI apps.

To describe ETL in detail,

Extraction – This part extracts data from uniform or diverse data sources.

Transformation – This formats or designs the data into the required type.

Load – The final part helps to move and store the data permanently at a location for long term usage.

ETL testing process

There is a process to perform ETL testing. Moreover, this testing is performed in five different stages:

  • Locating data sources and needs
  • Data acquisition
  • Implement business logic and dimensional Modeling
  • Develop and populate data
  • Moreover, create intuitive Reports

Informatica PowerCenter is an important and powerful ETL testing tool. And a unified data integration platform for any business.

Let us discuss how to perform ETL testing particularly in Informatica.

The important aspects that are essential to cover within Informatica ETL testing are as follows:

  • Testing the Informatica workflow functions and its components; all the changes used within the primary mappings.
  • To verify the data completeness (i.e. Making sure if the data is loading to the destination without any curtail and data loss).
  • Verifying whether the data loads to the destination within stipulated time limits (i.e. workflow performance assessment).
  • Make sure that the workflow does not allow any invalid or faulty data to get into the destination.

Categorizing of ETL Testing in Informatica:

To understand much better and for ease of the tester, ETL testing within Informatica is divided into two major parts –

  • High-level testing
  • Detailed testing

High-level testing in Informatica:

In this type of testing,

  • Users can verify if the Informatica workflow and linked objects are valid or not.
  • Check if the workflow completes the process successfully on running.
  • Moreover, check the validation of all the required sessions/tasks is being performed within the workflow.
  • Assert whether the data is getting loaded to the expected destination directory and with the required filename, etc.
  • Overall, we can say that high-level testing consists of all the basic prudence checks.

Detailed testing in Informatica:

In this test,

  • Users will go in-depth to confirm whether the logic applied in Informatica is working according to expected. In terms of its results and execution.
  • The user needs to do the output data accuracy at the field level. This confirms that each transformation is operating well.
  • Check whether the record counts at each level of processing and ultimately if the target is as per expectation.
  • Observe in-depth elements such as source qualifier and destiny within source/target statistics of the term.
  • Make sure that the running time of the Informatica workflow is at par with the approximate run time.
  • Finally, we can say that the detailed ETL testing includes a stringent end to end validation of workflow and the linked data flow.

The following image will help you to understand the workflow easily.

Get practical experience of the ETL process and its usage in real-time with Informatica Online Course through experts.



How to create ETL Test Case

ETL testing concept is applied to various tools and databases within the information management industry. The main objective of testing is to make sure that the data loaded from a source to target after business transformation is precise. Moreover, it also includes data verification at different middle stages that are useful between source and target.

While executing ETL testing, there are two documents that will always be required by an ETL tester are;

ETL mapping sheets: An ETL mapping sheet include all the important information of the source and target tables. It also includes each and every column and their look-up within ref tables. An ETL tester needs to be pleasant with SQL queries. ETL testing may include writing large queries with many joins to approve data at any stage of ETL. Moreover, ETL mapping sheets offer noteworthy help during writing queries for data verification.

DB Schema of Source/Target: This feature should be kept available always to verify any detail within mapping sheets.

ETL testing tools

The following are the top ETL testing tools that help in the testing process in real-time.

  • RightData
  • QuerySurge
  • Datagaps ETL Validator
  • ICEDQ
  • Xplenty
  • Informatica Data Validation
  • QualiDI
  • GTL QAceGen
  • SSISTester
  • TestBench
  • DbFit
  • AnyDbTest
  • Talend Open Studio for DI
  • Codoid’s ETL Testing Services
  • Data Centric Testing

Out of the above, a few of these tools we are going to discuss in detail hereunder.

RightData

This is a self-service ETL testing tool built to help business and technology teams effectively. It uses the automation of data to provide quality assurance and data quality control processes.

RightData’s inherent interface allows users to prove and reconcile data between datasets. This makes it anyway even the differences in the data model or the data source type. Besides, it is built to work efficiently having high complexity and large volume data platforms.

Features of RightData

  • Using this testing tool, users can execute field to field data comparison. Nonetheless, the contrast within the data model, structure between source and destination.
  • Moreover, it comes with a pre-supplied set of validation rules along with a custom business rule builder.
  • RightData includes bulk comparison capacity to ease the technical data reconciliation across the project terrain.
  • It has robust caution and notification ability initiating from emails. This is via automatic building the incident management tools of user choice.

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Xplenty

The tool is a data integration, and ETL platform useful in testing. This cloud-based platform makes data processing smoother. It also provides an instinctive graphic interface to execute an ETL, ELT, or a copy of the solution. Using the Xplenty tool, users can be able to perform out-of-the-box data modifications.

Features of Xplenty

  • The tool’s workflow engine will help users to adapt and plan data pipelines.
  • Moreover, users will be able to apply critical data preparation functions with rich expression language.
  • It includes the functionalities like plan jobs, monitor job progress, status as well as sample data outputs, etc. Also, it ensures accuracy and validity.
  • This platform lets users combine data from above 100 data stores and SaaS apps.
  • Xplenty provides both low-code or no-code options to the users.

Informatica Data Validation

This Data Validation tool is an ETL Testing tool based on GUI. The tool is useful to extract, transform, and Load (ETL) testing very well. Besides, the testing involves a comparison of tables before and after data relocation.

This testing type ensures data solidity at high. It means the volume of data is accurately loaded and is in the relevant format into the target system.

Features

  • The Informatica data validation tool is an extensive ETL Testing tool. It doesn’t need any coding skills.
  • It provides automation testing in the duration that ensures the data is reached correctly to destiny. And it is in the relevant format to load in the target system.
  • Moreover, the tool helps to finish data validation and reconciliation within the testing and output environment.
  • Furthermore, it minimizes the risk of inserting errors during modification. And it avoids bad data to be transmitted into the target system.

QuerySurge

It’s a tool built for testing of Big Data and Data warehouse with large volumes. It ensures that the data collected and loaded from the source device to the target system is accurate. And the same is as per the format need. Moreover, any issues or obstacles are located very quickly by the QuerySurge tool.

Features of QuickSurge

  • This is an automation tool useful for ETL & Big data testing.
  • It enhances data quality and speeds up the testing cycles.
  • Besides, the tool validates data with the Query Wizard during the test.
  • It saves time & cost by automation and reduces manual efforts. It also plans tests for a particular time.
  • QuerySurge supports ETL Testing across different platforms. Such as IBM, Oracle, Microsoft, SAP, etc. giants.
  • Moreover, the tool helps to create test structures and test suit along with configurable reports without SQL skills.
  • It produces email reports using an automation process.

iCEDQ

This is an automation ETL Testing tool particularly build for the problems faced within a data-centric project. Such as a data warehouse, data migration, etc. Besides, the iCEDQ tool executes checking, validation, and reconciliation between the source and target machines.

It also makes sure if the data is complete after the relocation. And it circumvents bad data to load into the destiny systems.

Features

  • iCEDQ is a distinctive ETL tool for testing that collates millions of databases rows or files.
  • It helps to locate the exact row and column that involves any data problem.
  • It sends notifications to subscribed users after performance testing.
  • The tool supports regression testing also well.
  • iCEDQ supports multiple databases and has the ability to read data from any database.
  • It links with a relational database, any JDBC compliant database, flat files, etc. easily.
  • It is based on particular columns under the database. Thus, the iCEDQ compares the data within memory.
  • Moreover, the tool is built for ETL Testing, Data Relocation Testing, and Data Quality checking, tasks.

Data Gaps ETL validator

The ETL Validator tool built for platforms Testing Big Data and ETL. Besides, this is a solution for data combination projects. The testing of such a data integration project involves different data types, large volumes, and multiple source platforms.

The tool helps to control such problems with automation that further helps to minimize the cost and to reduce efforts.

Features

  • This includes an inbuilt ETL testing engine that compares lakhs of records from different databases or flat files.
  • The Validator tool is a data testing tool particularly built for data warehouse testing with automation.
  • It includes a Visual Test Case (VTC) Builder having a drag and drop facility.

Benefits of using Informatica as an ETL testing tool:

The below points explain a few benefits of using Informatica as an ETL testing tool. The tool is much popular because;

  • It includes a high “go live” success rate with 100% utility.
  • Informatica includes the capacity for allowing Lean Integration.
  • The tool has a moderate cost compared to other ETL tools in the market.
  • The tool comes with an internal job planner. Therefore, there is no need for a third-party planner apart like a few other ETL tools do.
  • The availability of easy training and tools made Informatica more popular in the market.

Types of ETL Testing

ETL Testing is classified into different categories depending on the testing process that is been followed.



Production Validation Testing:

This is often known as Table balancing or product reconciliation testing. It is executed on data before or during transmits into the production system in the exact order.



Application Upgrade:

This is useful to verify if the data is collected from an older or new application or data repository.



Source to Destination Testing:

The kind of ETL Testing executed to validate the data values after data change or modification.



Data Completeness Testing

This type of testing helps to check if the assumption data loads at the relevant target as per the predefined standards.



Data Transformation Testing:

Many SQL queries need to run for each and every row to check data modification standards.

There is another kind of testing suite available that is Database testing. Let us have a look at the different kinds of ETL Testing with respect to database testing.

The following are the different types of ETL Testing related to Database Testing:



Constraint Testing:

Testers should test whether the data is mapped exactly from source to target while verifying. For this testers need to focus on some key points in this regard.

These are:

·    NOT NULL

·    UNIQUE

·    Primary Key

·    Foreign Key

·    Check

·    NULL

·    Default



Duplicate Check Testing:

Source and destiny tables include a large amount of data with often-repeated values. In that case, testers need to follow some database queries to locate such data replication.

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Navigation Testing:

Navigation testing involves the GUI of an application. The user finds an application user-friendly when he gets easy and pertinent steer throughout the system. Moreover, the tester must focus on evading irrelevant navigation from the user’s point of view.



Initialization Testing:

This kind of testing helps to verify the combination of hardware and software needs along with the platform it gets deployment.



Attribute Check Testing:

This type of testing executes checking if all the attributes of both the source and destination systems are equal.

From the above types of testing one can consider that ETL Testing is very similar to Database Testing. But the fact is that ETL Testing is effective with Data Warehouse Testing only.



Responsibilities of an ETL tester

The main responsibilities of an ETL tester, divide into three different divisions;

  • Stage table/ SFS or MFS category
  • Business change logic applied category
  • And destination table loading from the stage file or table after applying a change.

Some of the other responsibilities of an ETL tester are as follows;

  • The tester Test an ETL software well
  • Test components/tools of ETL data warehouse
  • Perform backend data-driven test as must
  • Build, design, and perform test cases, test schedules, and test harness
  • Locate the problem and provide solutions for complex problems
  • Support requirements and design particulars well.
  • Writing SQL queries for different plots such as count test.

Final Words

Thus, we have gone through the process of ETL testing using Informatica and its useful benefits. I hope you got an overall idea of the testing process within this technology. This is one of the best tools for ETL testing. To get more updates in this section, reach to Informatica Online Training and get a professional skill.