Uploaded on Dec 5, 2022
HCL OneTest Data generates mock data for testing environments and generates synthetic data sets without the risk of data leaks or privacy issues, all on demand. With a powerful built-in API, testers can generate data in a number of different ways including the use of predefined datasets, data generation rules, or with custom data generation scripts for any environment. Here you can check how to do so https://www.hcltechsw.com/wps/wcm/connect/7f39ff1f-8041-452c-9d3d-8759df68a98e/HCL+OneTest+Data.pdf?MOD=AJPERES&CONVERT_TO=url&CACHEID=ROOTWORKSPACE-7f39ff1f-8041-452c-9d3d-8759df68a98e-nkHFQE4
Develop Mock Data Needed for On-Demand Test
HCL OneTest Data DEVELOPING THE DATA NEEDED FOR TESTING ON DEMAND Making sure the right data is on hand for testing can be demanding. A traditional approach replicates existing data from production systems and uses it in test environments. With GDPR and other privacy regulations in effect, this type of testing has become much riskier, especially where personal data is concerned. There are also many occasions where there is not yet a production system, and so no production data to use. HCL OneTest Data generates mock data for testing environments and generates synthetic data sets without the risk of data leaks or privacy issues, all on demand. With a powerful built-in API, testers can generate data in a number of different ways including the use of predefined datasets, data generation rules, or with custom data generation scripts for any environment. DESIGN CUSTOM DATA MODELS GENERATE SYNTHETIC DATA IMPORT PRE-DEFINED DATA MODELS Benefits Reduces Data Privacy Risks Increases Testing Efficiency Avoids using real data and Provides predefined data sets violation of data privacy and real-time data generation for improved efficiency and Provides Comprehensive accuracy Test Data Creates all the volume and Avoids Production System diversity of data required to Intrusion cover any test scenario Removes the need to extract real and potentially sensitive information Capabilities Features an Open Modeling Easily Seeds Sample Data Mechanism Uses Excel or CSV reference Provides flexible methods files to upload sample data to model the data you need including regular expressions, Invokes Data Generation in the weighting and rules CI/CD Pipeline Uses HCL UrbanCode Deploy Powerfully Built-in API or Jenkins for real-time Explores, models, and automated data generation generates data through REST- based APIs Publishes Data to Relational Databases Flexible Generation File Includes all databases that Formats support JDBC Produces data in CSV, Excel, JSON, XML, text and binary formats /// hcltechsw.com/onetest
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