At a glance
Data mapping is a process used to identify how customer data is handled, stored, and transmitted.
Records of processing activities (ROPA), a subset of data mapping, are a requirement of GDPR Article 30.
Manual data mapping presents some challenges, but the benefits to privacy law compliance far outweigh and potential downsides.
Table of contents
What is data mapping?
In the context of privacy, data mapping is a process used to identify how customer data is handled, stored, and transmitted—giving organizations clarity about how personal data is stored, used, and shared.
A key part of compliance with privacy laws like the General Data Protection Regulation (GDPR) and the Consumer Privacy Rights Act (CPRA), data mapping supports the fulfillment of consumer data requests and the completion of data protection impact assessments.
In addition to facilitating privacy law compliance, data mapping also makes assessing compliance much easier. With a complete data map in hand, companies can use their data map to identify where personal data is stored within their tech stack and whether it’s being used for any risky processing activities.
Data mapping can also help improve customer trust by providing transparency on how information is being processed and secured.
As the legal landscape around data privacy changes and evolves, data mapping has become critical to effective compliance. Below we’ll cover how data mapping fits into two key privacy laws: GDPR and CCPA.
Data mapping and GDPR Article 30
GDPR Article 30 outlines an organization’s legal obligation to create and maintain records of processing activity (ROPA). The goal being that organizations are transparent, systematic, and accountable when it comes to data collection, usage, storage, and processing.
ROPA documentation provides a detailed overview of how an organization processes personal data, including how data is stored, managed and transferred, as well as details on any third parties involved in the process.
Using data mapping, organizations can clearly identify how customer data is handled, stored, and transmitted throughout their organization. A complete data map can also reveal how/when third parties are coming into contact with personal data—one of the many things that must be included in a ROPA document.
How is data mapping used?
Data mapping can be used across a variety of industries, including healthcare, finance, retail, manufacturing, and more. It can be used to match patient records across multiple systems or to map customer information between different databases.
It can also be used to integrate legacy systems with newer technologies, or to migrate data from one system to another. However, in the context of privacy, data mapping is most often used to:
Create a real-time view of all a company’s data systems and the personal data within
Reduce risk by surfacing sensitive data
Make day-to-day privacy tasks more efficient by providing a single source-of-truth, which in turn facilitates data subject request fulfillment.
Data visibility is still a challenge for most companies
Our research shows most data visibility efforts are slowed by system sprawl, reliance on manual processes, and insufficient resources. As a result, a staggering two-thirds of companies still don’t have an accurate picture of the data they hold.
Challenges of data mapping
Data mapping can present a number of challenges. One of the most significant is that data mapping requires a significant time and resource investment—as organizations need to compile detailed records of every single instance in which personal data is used, stored or processed across their tech stack.
Additionally, GDPR Article 30 stipulates that organizations must keep these records up-to-date, meaning regular reviews are necessary. Any changes or updates need to be carefully documented, requiring further investments in staff and resources.
Organizations also need to ensure that any third party data processors are compliant with Article 30. As such, large organizations may find themselves dealing with multiple sets of records belonging to different providers and vendors.
Another data mapping challenge is the sheer complexity of tracking down all personal data and sources across a sprawling ecosystem. According to a recent report:
The largest organizations, those with over 1,000 employees, use an average of 177 SaaS applications.
Data needs to be mapped from its source or origin to its destination, regardless of whether the data remains static or changes over time. This process can quickly become overwhelming due to the vast amounts of data involved and the necessary precision required.
Benefits of data mapping
Data mapping is an essential tool for maintaining privacy in today's digital age, helping companies to:
Better comply with privacy regulations
Get a comprehensive view of their data landscape
Identify potential security or privacy risks
Respond quickly to changes in privacy regulations
Protect the personal information of customers and other stakeholders
By understanding what personal data is being collect, where it lives, and how it's being used, organizations are better equipped to comply with modern privacy laws like GDPR and CPRA.
Data mapping also helps organizations respond quickly as these regulations shift and new data privacy laws are passed.
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Data mapping is an essential tool for any business that needs to transfer or integrate large amounts of data between different systems. By using data mapping techniques businesses can ensure accurate transfers while reducing the risk of errors due to mismatched fields.
Transcend is the platform that helps companies put privacy on autopilot by making it easy to encode privacy across an entire tech stack.
Transcend Data Mapping is the only solution that goes beyond observability to power your privacy program with smart governance suggestions. Get unified data management through automated scanning, data silo discovery and advanced data classification, all in a collaborative platform.
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