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    Data Masking in Non-production and Test Environments in SAP

    Security attacks and personal and company data breaches represent one of the most critical risks to organizations. Recently, with more government and industry controls on companies being put in place, there is a greater tendency to infringe data protection regulations without understanding the consequences. Using SAP production data in non-production SAP environments is critical for making ‘actual’ business tests and making case decisions. Consequently, violations in tests and quality control environments will cost millions to rectify, causing irreparable harm to the company’s image.

    Were you aware that providing live production data in non-production conditions will no longer be legal? When a company wants to use consumer data in non-production environments, upcoming European Union data protection regulations require individual customer consent. These regulations’ effects and costs will be significant, and compliance regulations are ready for implementation by the data protection authorities across Europe.

    This article outlines the meaning and importance of data masking and explains the implications of using production data in non-production and test environments of SAP.

    Data Security Threats: A Grim Reality

    Security threats are on the rise, particularly since the second half of 2019, with significant effects on society with trade. Hackers are trying to gain access to personal data and confidential information relating to employees, pricing conditions, and financial details. Given the rapid growth in data volumes compounded by cloud, electronic payment, mobile technology, and social media, data breaches will continue to pose a significant threat in the times to come to large and small businesses.

    Organizations have been trying hard, usually unsuccessfully, to keep their confidential data secure. Attackers are continually improving their skills to find new ways to exploit security loopholes. The reputation and brand images of corporates are at risk, and as we know, they hold immense significance. When confidential records are breached, massive government fines and penalties may be imposed, and substantial legal costs accrue. According to research, internal data breaches and lack of technological expertise are significant risks to data security. It remains the responsibility of organizations and their employees to follow suitable policies and procedures in managing data. Yet, the human factor is, without doubt, the weakest link in the data security chain.

    Data Masking in SAP

    Many firms are unaware that the cost of implementing a solution to secure sensitive data pale compared to the enormous costs associated with a security breach.

    In this context, it is pertinent to understand what data masking is. It refers to the method of blotting out actual and sensitive data within a database to ensure full confidentiality and non-exposure of personally identifiable information (PII). This helps companies meet mandatory compliance obligations under HIPAA, PCI, GLBA, and other data protection legislation. Data masking technologies should fulfill a strict yet straightforward rule: masked data should be realistic and quasi-real — that is, the data should follow the same business rules as real data. It ensures that all applications perform as if the masked data are real. Data masking does not impair the ability of a user to use applications properly. SAP data masking makes it challenging to distinguish confidential information in the SAP environment, but stays compatible with overall system behavior. This allows for the development of secure and efficient test and QA environments.

    SAP data masking is a practical approach to data security in SAP environments. In addition to other security controls such as encryption, access control, monitoring, and audit controls, data masking policies can also be applied. Each such measure plays a crucial role in ensuring data security in a production environment. Data masking is becoming the best practice to secure sensitive data in a non-production environment, however. Masking data is intended to:

    • Minimize the risk of disclosure resulting from access to the data.
    • Secure intellectual property and trade secrets for businesses.
    • Comply with the Government and Auditors’ administrative standards.

    Conclusion

    We have tried here to highlight the idea of SAP data masking in relation to the importance, effect, and the implications of using production data in non-production and test environments in SAP. Considering the substantial rise in data security breaches, all companies must remain compliant with industry regulations and government policies/legislation when exchanging production data in non-production environments. Thus, data masking in such a scenario is essential to ensure data security.

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