What is meant by test data management?
Test Data Management (TDM) is the management of data that is crucial for satisfying the requirements of automated test processes. This test data management also guarantees the quality of data and its availability at the correct time.
What are the best methods for test data management?
It is very important for any organisation to maintain an excellent team with a group of testers. Because having such a team, bugs or errors can be removed from the product at the initial level before delivering the product to the client.
Entire organisations have to keep the focus on providing resources to the team, which impacts on improving the efficiency in finding the errors in a product. Below are the best practices of test data management, which are very beneficial in testing leaders.
1. Set clear performance metrics: Testers, test managers should focus on measures related to defect detection and troubleshooting. High levels of measurements like test case speed, can be offset with singular performance tracking and explicit imperfection measures to provide a more balanced perspective on testing.
2. Consider new testing technology: Testing managers have to take an objective and their existing Quality Assurance testing tools. So it might be viewed as new test case software or refreshing a reporting platform that highlights and cross-checks with specific estimations.
3. Report, analyze, and educate: Test managers have to focus on reporting and analyzing the data to target particular issues affecting the measurement of efficiency. This furnish test manager with an in-depth understanding of the pros and cons. This goes for forms just as individual exhibitions and educational efforts.
Industries that use Test data management ?
Test data management is useful for large organisations. These organisations use large amounts of data that contain private information.
Mostly such type of confidential data is used by various industries like educational, healthcare industries, government sectors, and various research institutes. Such kind of data needed masking. When the data is masked, it is very typical or hard to steal sensitive data from any organisation.
What are the uses of test data management?
- It helps in good software quality product testing
- It reduces the security risks in various organisations
- It creates cost-efficient software
- It also helps in the identification of bugs
Why Test Data Management Important?
Test data is very important so that it builds trust over the customers. When testing is done to a particular product, it helps in finding bugs, and testers can fix such bugs before handing it to clients. Below are the three reasons why test data Management is important.
- Improves the customer management relationship
- Avoid copies of test data
- Lowering costs associated with finding bugs
What are the top 5 reasons for test data management?
- Data Protection Legislation
- Cloud Testing
- Service Virtualisation
- 3rd Party Integration
What are the Best Test Data Management Tools In 2020
Here is a list of data management tools trending in present marketing
DATPROF: Data prof tool helps in data generation, subsetting, and data provisioning platforms.
Informatica: Informatica is a tool that provides automated data generation, subsetting, masking, and data connectivity. This tool finds a sensitive data location automatically.
It also provides the non-production data set, which is required for the development team. And also, it supplies the data, which increases the test data security.
CA Test Data Manager (Datamaker): Computer associates own this product. The functionality and design of this CA Test Data Manager is very simple, and this is a tool that generates high synthetic data solutions.
This also produces, saves, and even reuses the test data in its repository. This tool is also called an on-demand tool, which means you can access the data whenever you are in need.
Compuware’s: Using this tool, you can create the test data easily. And also quickly generate, translate, mask, and validate the test data. Moreover, it fulfills the condition of the mainframe test, which is the additional feature of the tool. It provides data privacy and also suitable for all types of standard files.
InfoSphere Optim: It is a product of IBM. It supports two service facilities. These facilities include
- On-demand service
This tool provides real-time data testing, right-sized test data, which automates and optimizes the test data management. It provides the test data to developers and testers, which is an on-demand service.
It also reduces the cost and speeds up the application, and it also increases the speed delivery of application projects.
LISA Solutions: This is a testing tool which automatically creates and generates the data set with the high-level function accuracy. This tool imports the data from various types of files like xml, excel, etc.,
Both the tester and developer can easily change the values of test data and integrate them into a single.
This automatic data masking helps in protecting sensitive data without violating any security policies. Features like dynamic stabilization that approves the test information as indicated by the business rules. The additional functionality of this tool which self heals the test data that builds the reasonability of virtual test information.
Delphix: Delphix is a tool that provides a feature with quick testing and high quality. Redundant data is shared through all phases, like developing, training, testing, and reporting. Sharing of such data, in other words, is called data virtualization.
Virtual data gives complete and real data sets in less time with low spaces. This tool improves productivity by the configuration of databases, applications, and automatic delivery, and also this tool reduces the cost of storage. This tool supports and works on both public(free services) and private(paid services) cloud infrastructure.
Solix Enterprise Data Management Suite (Solix EDMS): This tool automatically makes the test data subsets for development, training, development, masking, outsourcing, and testing. This decreases the expense of infrastructure. It also reduces time and capacity.
Original software: This tool protects and regulates the data. This tool easily creates the test data that reduces the risk that is associated with disk space, data verification, and confidentiality of data.
TechArcis: This is a useful tool in creating the test data automatically, which is accurate, secure, and complete. Masking the data increases the security that maintains referential integrity.
Test Data Management Best Practices for Automation
Following are some test data practices for automation:
- Externalise test data
- Generate unique prerequisite data through automation
- Consider all test environments
Test Data Management for Information Security
Data contains some confidential and sensitive data such as of employee details, organisation details, products details, etc.,
There are certain strategies in securing the information
Test data Management – Checklist
Below are the checklist of test data management:
- Identify the common test data elements
- Masking, Aging and archiving of test data
- Allocation of test data and Prioritization of test data
- Generating reports, dashboards for metrics
- Creating, implementing the business rules
- Building an automation suite for preparation of master data
- Archiving, Masking and versioning aging of data
Test Data Management Best Practices:
Below are the Five Steps to Better Test Data Management practices
- Discover and understand the test data: Identify the test data and understand the test data, as the data lies on various resources in different formats.
- Extract a subset of production data from multiple data sources: Extract the data which is present in large forms in different formats that are obtained from multiple data sources. There are certain approaches in identifying and extracting the data subsets.
- Mask or de-identify sensitive test data: Mask the sensitive data which is very confidential that belongs to various industries. The data should be identified and masked because the data may contain details of employees or information about clients.
- Automate expected and actual result comparisons: It is necessary to identify the data anomalies and consistency while testing this estimate in measuring the quality of the application.
- The proficient method to achieve this objective is by utilizing automated capability for comparing the standard test data against results from progressive test trials. Automating these comparisons helps in saving time while maintaining a consistent, manageable test environment.
- Refresh test data: As the testing process goes on certain phases, data diverge from the baseline that leads to a false or less optimal test environment. So to overcome these issues refreshing the test data is necessary. By refreshing the test data, the efficiency of testing is improved while maintaining a sensible, reliable test environment.
How to organize Test Data in End-to-End Test Automation
End to end Test automation is necessary, which is the final and crucial process to check whether the software is working correctly or not. Testing should be done under some phases with certain strategies. While testing, it returns any flaws or any bugs in the data.
Here below are some strategies which deal with test data.
- Creating test data during test execution
- Query test data prior to test execution
- Reset the test data state previously or after a trial
- Virtualizing the data layer
Final thoughts: The Bottom line of Test Data Management is, it is beneficial for testing the performance of projects.
It additionally guarantees that data with enormous volume can be made productively and quickly for the testing procedure. Most importantly, Test Data Management helps in lessening the costs, time, and endeavours.