Best Test Data Management Tools in 2023
Are you looking for Test Data Management Tools?
Here we will list out the best tools which give you high-quality data for your testing needs.
Through this article, you can get information on what is test data management, top TDM tools, and the following.
What is Test Data Management in Software Testing?
Test Data Management is the process of creating non-production data that reliably mimic actual data for fulfilling the needs of automated test processes with no or little human intervention. Based on the non-production reliable data, testers and developers can perform system tests rigorously.
What are Test Data Management Tools?
Test data management tools help organizations increase the quality of the software. These tools generate synthetic data, perform data profiling, extract and scramble data, and refresh data. Developers and testers will be more efficient in project development and testing by using these tools.
Top Test Data Management Tools
#1. K2View Test Data Management
Best for enterprises with numerous data sources and/or legacy systems
With K2View Test Data Management, test data subsets from production sources can be provisioned quickly with referential integrity, regardless of the number of systems, technologies, and environments. Shift-Left Testing can be enabled by embedding the solution in a DevOps CI/CD pipeline.
Testers define their desired test data sets using the solution’s self-service portal. A tester may request test data related to 250 customers in a certain zip code with at least two children and an outstanding debt greater than a specific amount.
Sensitive PII data is protected before it is delivered using in-flight data masking. Several additional features are also available, such as the ability to manufacture synthetic test data with referential integrity, roll back the version of test data, reserve subsets of test data for specific testers, and more.
A web-based interface allows testers and administrators to schedule tests, track execution results, and view execution status.For a free demo or proof of concept, contact the K2View team via the website.
Features:
- A self-service portal that allows testers to provision test data on demand
- Extraction of production data subsets based on user-defined search criteria
- Versioning and searching of data sets in a test data warehouse
- Generating synthetic test data, ensuring referential integrity
- Masking and validation of data in compliance with privacy laws
- Automation of DevOps using a web service API
Why K2View is the best test data management tool
K2View TDM is not constrained by the number of data sources and technologies used. Due to its patented architectural design, the tool handles large-scale, complex enterprise environments with high performance. Numerous data masking functions are available out of the box, with referential integrity preserved by design.
#2. Informatica TDM Tool
Informatica Test Data management tool allows test teams to generate test data sets for their testing needs. Its key features include improves the testing productivity, sensitive data discovery and classification, data warehouse with self-service, data subset, data masking, pre-built application accelerators, and monitoring and compliance reporting.
#3. IBM InfoSphere Optim
IBM InfoSphere Optim tool helps to optimize and to automate processes that create and manage nonproduction data. It allows testers to create production-like test environments. IBM test data management tool supports continuous testing, and agile requirements for development. Developers and testers can access and refresh data on demand to improve operational efficiency while providing more time in actual testing. Its key features include manages data at the business-object level, accesses data analysis capabilities, enforces test data management software policies, and automates data comparisons and analyzes results.
#4. Microfocus Data Express
Micro Focus Data Express is to manage the test data environment. It improves test results, reduces testing costs, secures customer data from loss or misuse, and enables accelerated delivery and privacy compliance. It helps organizations to optimize and to automate processes that create and manage production-like test environment data. Its features include reduces the time required for extracting large amounts of distributed data needed for testing, accelerates application testing, reduces storage requirements, reduces costs through shared data extraction rules, and supports data privacy and security.
#5. Delphix
Delphix Test data tool automates the steps for provisioning test data such as target database initialization, configuration, and validation. Its key features include the end-to-end masking process by automating the discovery and auditing of sensitive data, protect sensitive data without compromising speed and agility.
#6. Datprof
DATPROF platform helps developers and tester to create and request their test data using the Detprof self-service portal. Its key features include generate synthetic test data, mask privacy-sensitive test data, subset the test data you need, and automate test data provisioning. It integrates and automates various test data processes within your CI/CD pipeline to shorten time to market.
#7. Test Data Manager (formerly CA Test Data Manager)
Test Data Manager helps organizations automate test data management, deliver test data faster, create synthetic test data from scratch, shorten test cycles from weeks to days, and improve compliance
#8. SAP Test Data Migration Server:
SAP Test Data Migration Server is a data extraction tool that transfers relevant business data from your SAP production system to your development, test, quality assurance, or training system. SAP test data management tools allow you to create easy to maintain production-like environment. It helps you to reduce data volume, scramble/eliminate sensitive data, automate & reduce runtime of data refreshes, allow functional teams to transfer subsets of data.
Conclusion
These tools help you to leverage a test data management strategy to subset production data while masking sensitive information.
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