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Published on April 29, 2021 AUTHOR - PRIVACY RESEARCH TEAM
The consistent increase in frequency and severity of data breach incidents, coupled with the introduction of data privacy regulations such as GDPR and CCPA (recently amended by the CPRA), are encouraging organizations to revisit their privacy operations and how they handle their consumers’ personal information.
The quest for better handling, management and protection of consumers’ personal information begins with fully understanding a concept called “Data Mapping” and understanding what a data mapping activity under the CCPA would entail.
But first, what is Data Mapping? Rehan Jalil, CEO SECURITI.ai, in his book titled "PrivacyOps: Automation & Orchestration for Privacy Compliance” defines data mapping as, “A system of cataloging the data collected by the organization, helping identify how that data is used, stored and processed, and how that data travels within and beyond the organization.
Thus Data Mapping is the process of creating a map of how data is managed across your organization. Without undertaking this activity, organizations would not be able to keep track of the personal information they collect from their consumers, where the personal information is stored, what type of personal information is stored or provide adequate privacy and security controls to protect that personal information.
In modern organizations there are multiple data collection and processing elements combined with in-house and cloud-based application and storage infrastructure, with highly fluid data sharing and processing agreements in place. With more than 80% of enterprise workloads now moving to the cloud, organizations are finding it hard to document and track the flow of information across cloud assets.
In most organizations, data catalogs and maps are hidden away in outdated spreadsheets and Powerpoint or Visio diagrams, making it impossible to bring clarity to this gigantic mesh of interconnected interfaces, systems, and processes. Also, without a collaborative documentation and knowledge sharing environment, it is typical for such business process knowledge to get locked up in the minds of subject matter experts, making it nearly impossible to build and maintain an accurate record of data.
This is where the PrivacyOps data mapping platform can help. By providing a secure privacy portal with a collaborative, easy-to-use environment powered by AI powered advanced robotic automation and data intelligence, data mapping has become a manageable exercise.
Generally, PrivacyOps methodology towards data mapping works on the back of the following 4 steps:
Data mapping maturity is the level of automation an organization wishes to incorporate within their PrivacyOps Data Mapping exercise. The higher the level of automation the higher the maturity level. There are 3 levels of data mapping maturity and we will discuss these individually to help you understand where your organization stands.
This is the ground level for any organization's data mapping processes. This includes gathering data assets, creating data catalogs, conducting internal assessments and assessing risks associated to the data and third-parties. This level requires minimal and basic automation helping organizations transition into using the PrivacyOps data mapping platform. Maturity Level 1 includes:
While gathering data from surveys and forms from stakeholders is a good first step, many gaps may still arise in this approach. Inputs provided may not be complete, new data assets may require periodic monitoring, and assets may evolve and change over time. Organization’s can ensure accuracy with continuous data scanning and discovery in Maturity Level 2 in which an organization’s data assets and records within the data catalog are automatically updated and risk assessments and workflows can be triggered by the results of these scan jobs. To ensure the accuracy of the information provided, organizations can use Maturity Level 2 automated data mapping to:
Securiti’s Data Mapping Automation simplifies the migration journey providing a comprehensive PrivacyOps framework for all your data compliance needs with Robotic Automation. People Data Graphs (PDGs) can be created within data maps to link personal data to its user identity enabling automated DSR fulfillment and other privacy compliance functions. Organizations can:
CCPA applies to certain businesses who are operating in California or collecting personal information of the residents while doing business in California, and it requires organizations to be responsible and accountable for the personal information they collect. This is not possible unless a CCPA compliant data mapping activity is conducted. CCPA compliant data mapping activity is required by an organization for the following reasons:
With data growing rapidly and regulations such as the CCPA encouraging organizations to keep track of their data, organizations will need to automate their processes in order to stay compliant with privacy regulations. Data mapping with manual methods is just not going to cut it given the added time, cost and resources - not to mention the risk of data sprawl and human error. In order to benefit from a truly robust data mapping structure, every business needs to adopt the PrivacyOps framework. Investing in such a framework will be immensely beneficial for any organization as it will be ready to comply with all data privacy regulations - not just the current ones such as the CCPA but also those that are in the pipeline, such as the California Privacy Rights Act (CPRA) which will go into force in 2023.