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
Comments