Organizations today face the daunting challenge of producing realistic and privacy-compliant test data at scale. AlterID offers efficient data generation capabilities with automated processes - an ideal solution for organizations wanting to generate privacy-compliant test data at scale
Organizations building digital product are constantly looking for ways to efficiently increase the pace of innovation, many have successfully integrated continuous integration and continuous development pipelines (CI/CD) and various working environments - usually : development environments for building, pre-production for testing and production environment for deploying apps and services, populating these environments with high quality test data is crucial for effectively ensuring the quality of the software build.
Enter privacy regulations, strictly restricting the collection and processing of personal data, in production but also in secondary environments, which pose the same significant risks of data breaches and privacy infringements, these risks are often higher in development and testing environment than in production environments due to relaxed technical and organisational measures aimed at protecting personal data, this is a problem no matter the size of the organization.
From a regulatory standpoint, GDPR's article 32 “Security of processing”, provides that the data controller shall implement appropriate technical and organisational measures to ensure a level of security appropriate to the risk to the rights and freedoms of data subjects, regardless of the environment in which the processing takes place - ie. Considering the risks related to protecting personal data in development, pre-production exactly as in any production environments.
The European Data Protection Supervisor (EDPS) leaves no doubt about it in its Guidelines on the protection of personal data in IT governance and IT management of EU institutions1, the guidance states that " In the testing phase, sampling of real personal data should be avoided, as such data cannot be used for purposes for which it was not collected and using it in testing environments may result in making personal data available to unauthorised individuals"
In its report Test Data Management Challenges2 KPMG highlights the six challenges to effectively deliver quality test solutions.
Developing and implementing safe test data management strategies requires tackling :
1. Data Coverage: Test data is usually generated manually, leading to gaps in test data coverage.
2. Data Updates: The lack of data update mechanism renders test automation inefficient and/or unable to support automation or agile initiatives.
3. Data Privacy: Identifying and protecting personally identifiable information (PII) as required by GDPR, in fact according to the principle of data minimisation and the principle of data protection by design and by default, personal data use for testing should be avoided where possible.
4. Data Versioning: Consistency in test data from one development sprint to another.
5. Complexity: Managing referential dependencies within complex data architectures is also a challenge manual test data generation can't effectively solve.
6. Governance: The lack of test data provisioning capability leaving the developer teams on their own to create and manage test data, resulting in poor data quality and unmitigated privacy risks.
Overall, to be effective, a robust test data management process should take into account all of the above challenges, in every step or the process.
AlterID addresses the difficulties involved with producing realistic test data while complying with privacy regulations, streamlining test data management processes, and decreasing compliance risks related to using real customer data for testing purposes.
Integral to AlterID Protect, uses advanced PII data detection capabilities, ensuring sensitive information is identified and masked appropriately during test data generation processes. By automatically detecting and anonymizing sensitive data, it ensures compliance with privacy regulations while keeping sensitive data secure.
AlterID fully automates the test data generation process by creating production-grade anonymized test data that are perfect replicas of your production data with guarantee referential integrity and formats. These replicas are re-freshed and synchronized on demand with production data so no changes are required to existing CI/CD pipelines and processes, providing organisations with the quality of compliant test data possible, while significantly expediting software testing processes.
AlterID Protect for non production environments delivers high quality compliant production-grade consistent data, fresh and accurate ready before every development sprint so you teams can focus on what matter the most for your organization, building great software.
AlterID's automated data generation capabilities will help you quickly generate large volumes of realistic test data, significantly reducing preparation and approval time to hours NOT days.
With test data cleared of PIIs and anonymized, ensure that your test data meet the highest privacy standards, by default, at all time.
AlterID seamlessly deploys through virtual machines into existing data architecture without any disruptions or changes to your test data management pipelines or workflows, providing you with a smooth transition toward privacy-compliant test data generation.
Protecting personal and sensitive data during development and testing has become crucial, creating massive challenges to reconcile fast paced innovation and privacy compliance. Traditional mitigation methods often require manual work and tend to create privacy exposures for organizations handling personal data.
AlterID Protect offers a pragmatic approach to make your development teams, your CISO, your DPO and your customers happy, reach out now and let's get privacy of our the way for your non production environments.
Footnotes
1. The European Data Protection Supervisor (EDPS) Guidelines on the protection of personal data in IT governance and IT management of EU institutions link
2. Test Data Management Challenges Report KPMG 2020 link
3. TDM 101 link
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