{"id":22358,"date":"2024-07-29T16:47:24","date_gmt":"2024-07-29T11:17:24","guid":{"rendered":"https:\/\/www.cigniti.com\/blog\/?p=22358"},"modified":"2024-07-29T16:47:24","modified_gmt":"2024-07-29T11:17:24","slug":"maximizing-efficiency-savings-test-data-management-framework","status":"publish","type":"post","link":"https:\/\/www.cigniti.com\/blog\/maximizing-efficiency-savings-test-data-management-framework\/","title":{"rendered":"Maximizing Efficiency and Savings with a Cutting-edge Test Data Management Framework"},"content":{"rendered":"

In today’s regulatory environment, organizations are compelled to adopt stringent security measures to mitigate the risk of PII (Personally Identifiable Information) data breaches in their production environments. However, the pressure to provision more test data in non-production environments, often sourced from production data, has introduced new vulnerabilities. The real risk of data breaches now lies in these non-production environments, highlighting the critical need for robust test data management (TDM) solutions. Such solutions enable organizations to provide unrestricted access to high-quality test data while protecting customer PII from breaches.<\/p>\n

Achieve Significant Time & Storage Savings with an Effective TDM Framework<\/h2>\n

An effective TDM framework adheres to best practices for data management, ensuring optimal performance and efficiency. Here are the core components of such a framework:<\/p>\n

In-Depth Requirements Identification<\/h3>\n

Leveraging deep industry knowledge, an effective TDM strategy begins with establishing complete requirements for test data, including the source, volume, complexities, data subset policies, and data synthesis needs.<\/p>\n

Holistic TDM Processes<\/h3>\n

Clearly defined data management workflows, policies, and procedures are essential for creating, loading, and protecting test data. Metrics are established to measure data health in each environment, minimizing the use of production data volumes whenever possible.<\/p>\n

Effective TDM Techniques<\/h3>\n

By creating optimized subsets of data, teams can use real data for effective testing while minimizing the required scale of data processing and storage. Techniques such as data masking, substitution, and encryption are employed to protect sensitive data.<\/p>\n

Data Management Tools and Expertise<\/h3>\n

A robust Test Data Generator tool reduces the manual effort of creating test data, thereby minimizing errors. This approach promotes the reuse of subset criteria and masking policies across multiple sources.<\/p>\n

Dedicated Data Governance Center of Excellence<\/h3>\n

A dedicated Data Governance Center of Excellence provides the necessary tools, resources, and expertise to accommodate every project\u2019s test data needs.<\/p>\n

In-Depth ETL Testing Services<\/h3>\n

Clients benefit from in-depth extract, transform, and load (ETL) testing services. Experts follow core ETL principles in TDM practices, ensuring high-speed and accurate results with the ability to reuse indexes and up to 70% of components.<\/p>\n

Benefits of Using a Comprehensive Test Data Manager with Packaged Applications<\/h2>\n

A comprehensive Test Data Manager offers a unique and extensive combination of capabilities, including data subset creation, masking, synthetic generation, cloning, and on-demand data generation. These features empower testing teams to meet their organization\u2019s demands for testing agility. This solution automates one of the most time-consuming and resource-intensive tasks in continuous delivery environments: the creation, maintenance, and provisioning of test data needed to rigorously test evolving applications.<\/p>\n

Two critical aspects of delivering excellent service are utilizing consistent test suites and having proper datasets for those tests. Implementing both ensures more consistent, timely, and reliable deployments of packaged applications. This is crucial because these applications are often relied upon in mission-critical areas such as enterprise resource planning, finance, inventory management, customer service, and sales.<\/p>\n

Experienced testers know the data they need – both the variety and volume – to test existing systems in production. However, collecting this data often requires significant support from operational groups and many custom, one-off scripts. Tools like a Test Data Manager solve this problem by offering data masking, versioning, and distribution capabilities. These tools help testers use the right data in the best places, effectively improving the quality of the applications being delivered.<\/p>\n

By automating test data management, teams can focus on enhancing application quality rather than being bogged down by data preparation tasks. This leads to faster development cycles, reduced costs, and higher-quality software. Ultimately, a robust Test Data Manager helps organizations achieve their continuous delivery goals more efficiently, ensuring that critical applications perform optimally in real-world scenarios.<\/p>\n

Harness a Robust and Unified TDM Solution<\/h2>\n

A robust and unified TDM solution enables continuous automation, shift-left defect identification, and faster test data creation while ensuring compliance with regulatory requirements. Coupled with advanced data assurance expertise, this tool offers significant benefits in terms of cost, compliance, and security.<\/p>\n

Key benefits of this TDM solution include:<\/p>\n