Few non-technological developments have impacted enterprise data management over the past several years as heavily as regulatory compliance changes. The evolution of data privacy and protection regulations forces enterprises like yours to re-evaluate how they collect and use data.
Why Are Regulatory Changes Becoming Even More Important?
Data privacy is poised for even further evolution. We are now moving into the era of hyper-personalized digital services powered by data-hungry artificial intelligence and machine learning (AI/ML) models. The stakes for regulatory non-compliance have never been higher. And regulators consistently demonstrate they will act when a breach occurs.
Enterprises like yours must act meticulously with their data. At the same time, they continue to create more engaging customer experiences. They also strive to boost productivity, accelerate their time-to-market, and remain competitive. Our belief is that those that re-evaluate their compliance standards will be most primed for success.
You must take steps to future-proof systems and processes against future regulatory compliance changes. This is the best way to ensure that you remain compliant with regulations — without dulling your competitive edge.
Compliance Changes: The Evolution of Data Privacy Regulations
Some forms of data privacy law have existed for over 40 years. But the adoption of the European Union (EU)’s General Data Protection Regulation (GDPR) in 2016 was a true watershed moment for data protection. It served as a blueprint for many data privacy regulations that have since been enacted.
Regulatory Changes by Geography
As of 2021, over 136 countries around the world have instituted data privacy and protection legislation, according to the United Nations Conference on Trade and Development.
Some laws, such as GDPR, Brazil’s General Data Protection Law (LGPD), and the California Consumer Privacy Act (CCPA), govern data privacy within political jurisdictions. Others govern specific industries, such as the United States’ Gramm-Leach-Bliley Act (GLBA) for financial institutions and the global Payment Card Industry Data Security Standard (PCI DSS) that regulates the protection of payment card data used by banks, payment processors, retailers and other firms. Still others, like the EU's Digital Operations Resilience Act (DORA), regulate areas adjacent to data privacy that still involve it.
Maintaining compliance with data privacy regulations can become complicated. You are often required to comply with the data privacy laws of multiple jurisdictions. GDPR, for instance, requires compliance from all foreign enterprises that collect any personal data from EU residents.
The U.S. possesses multiple data privacy laws, including GLBA for financial institutions, HIPAA for healthcare enterprises, and CCPA for enterprises doing business with California residents. And governing bodies are only cracking down further on data privacy compliance over time. Between January 2022 and January 2023, GDPR fines by aggregate increased by 50%, according to a report from multinational law firm DLA Piper.
How Compliance Changes Clash With Software Development
The proliferation of data privacy regulations impacts software development in several ways Regulatory changes shape how applications are designed, built, and maintained. Increasing market share and revenues remain the North Star for most businesses.
But it is now recognized that the software development that drives much of this growth uses a comprehensive approach that prioritizes user privacy, security, and compliance. Therefore, developers must be proactive in integrating these principles into their practices. It’s critical to build trustworthy and legally compliant software.
Yet data breaches and regulatory fines cause a reckoning with many enterprises. The Identity Theft Resource Center charted a 78% increase in total data breaches from 2022 to 2023, making 2023 the worst year ever for data breaches And each GDPR violation can cost up to 4% of a company’s annual global revenues or €20 million (about $22 million) — whichever is highest. This forces enterprises to take a closer look at their data. Data must comply with the data privacy regulations to which they are accountable.
This need for closer scrutiny of data is not without consequences. Many enterprises will need to reverse engineer their applications — as well as their development practices — to ensure that the data they use is compliant with all applicable regulations. Enterprises will also need to change data collection and data management processes to align more closely with compliance requirements, according to Forbes.
Enterprises like yours will need to act quickly and strategically in this area. Revamping these processes will naturally cause dramatic slowdowns in the pace of software development. But acting thoughtfully and future-proofing systems and processes for future compliance changes will save you both headaches and money.
How to Future-Proof Processes for Regulatory Compliance Changes
You should take the following steps to future proof your enterprise systems for compliance.
1. Find and Acknowledge Your Compliance Issues
Thoroughly audit your software development processes and identify compliance gaps. Acknowledge that these gaps are urgent issues. Compliance will only grow stricter as time passes.
2. Educate Your Team
Developers are the front line when it comes to building compliant software. Offer training sessions, circulate regular updates, and foster a culture of privacy awareness within your team. Make sure they are informed on privacy best practices. Consider delegating part of your team to stay up-to-date with new data privacy regulations and regulatory changes.
3. Embrace the Concept of Privacy by Design
Think about data protection, user consent, and security measures right from the start of development, instead of addressing them as an afterthought. Start building this thinking, a concept known as privacy by design, into your existing systems. Make it a core aspect of your software development.
4. Automate Compliance Checks
Use tools and scripts to run regular checks on your systems to make sure they’re keeping data compliant. This not only saves time but also provides peace of mind.
5. Employ A Disaster Recovery Plan For Compliance
Create a solid disaster recovery plan for possible instances of non-compliance. That way, if your organization finds itself on the wrong side of a privacy law, you will be able to minimize the damage.
6. Adopt Automated Data Masking For Your Test Data Management
When considering compliance solutions, efficiency and speed are key criteria to consider. Data masking is a streamlined data security solution that ensures compliance by irreversibly replacing original data values with fictitious but realistic equivalents. When automated, many databases can often be masked in minutes.
The Best Insurance Against Regulatory Changes
Data masking and anonymization are both techniques that enterprises use to protect their sensitive data. But masking delivers several benefits. Because it replaces your existing data with fictitious yet realistic data, data masking automatically ensures compliance with any data privacy regulation. Masked data does not, in fact, represent the information of an actual customer, partner, employee, etc. In this sense, data masking is also a great insurance policy against future compliance changes or new laws.
Masked data also benefits data security and development. It eliminates the risk of personal data exposure in the event of a data breach occurring in the non-production environments in which it is implemented. Masked data also retains most of the utility that its original version possessed. This allows developers to work just as easily with it as with original data values.
The rise of AI/ML has all but ensured that data privacy compliance will accrue even more importance in the years to come. Massive amounts of data are required for training these models. All of this data will need to comply with existing (and future) data privacy regulations.
As you adopt AI/ML into their operations, you will need robust processes in place to ensure that training data does not open your enterprise up to compliance lawsuits. By incorporating data masking into software development, you can ensure you retain full utility of your data — without any non-compliance risks.
The 2024 State of Data Compliance and Security Report
66% of organizations we surveyed are using static data masking to protect non-production data. Discover insights from 250 global leaders around sensitive data, compliance, masking, AI, and more.
How Delphix Future-Proofs Against Compliance Changes
Employing an automated data masking solution, such as Delphix Continuous Compliance, can help you effortlessly ensure airtight compliance, no matter what kinds of regulations emerge in the future.
Using Continuous Compliance ensures that data is irreversibly masked such that it is changed to fictitious data values that maintain referential integrity. That way, your organization can perfectly balance agility with utility in its masking processes.
Delphix static data masking can be applied to various sources. This includes databases — such as SQL Server and Oracle — and analytical sources — such as Snowflake and Databricks.
By leveraging Delphix static data masking, you’ll ensure data security, utility, and referential integrity across data sources.
Talk to our team today about how Delphix can help with your compliance operations.
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