Increasingly complex organisational landscapes are putting pressure on business systems to cope with growing amounts of data. As a result, companies that rely on enterprise resource planning (ERP) systems must ensure they have access to reliable and trustworthy solutions, capable of scaling with and supporting a growing volume of data.
To guarantee systems are operating as they should, organisations must invest in system testing and data masking to accurately understand the systems' capabilities without compromising security.
The business environment is in flux with new working models, accelerated digital transformation and mergers and acquisitions, creating complexity over the past 18 months. Using data effectively can help organisations manage change more effectively and continue to grow in a competitive marketplace.
One of the ways data can make a difference in organisations is in assessing the quality and performance of ERP systems. Using realistic data is critical to ensure the test results reflect real-world scenarios. However, using real data during the testing process is risky, potentially opening both data and organisations to external threats and exploits.
Using data masking during the testing process is a more secure way of assessing an ERP environment. In addition, it minimises the risk of exposing data as it de-identifies the information to ensure that sensitive data is anonymised for confidentiality when it is integrated into the testing environment.
Data masking is the process of creating fake-yet-realistic organisational data sets, which helps secure sensitive data from misuse, providing an efficient alternative for testing purposes. This is particularly valuable when leveraged for application development, as it lets data appear real and consistent without risking the potential for exposure of personally identifiable data sets.
Data masking is becoming increasingly important as the organisational landscape continues to evolve. Testing processes and environments must keep pace with digital transformations, and data masking is a highly leverageable tool that organisations can use to help streamline testing without compromising security.
However, annually masking data can be time-consuming. Additionally, cloning large databases to use in testing environments can be costly. Despite this, automated data masking solutions deliver a more cost-effective method of assessing organisations' systems and processes.
Preparing data for testing environments can eat up a significant amount of time. Automated solutions help mitigate this by reducing the amount of time and resources required without creating security risks. Data masking is essential in today's environments, and using more affordable, automated data masking solutions in the testing environment can make this even more valuable to organisations.
Automating data masking also accelerates testing, shortens the timeframes for change processes and development, and leads to faster, more effective business decisions.
