GDPR Compliance Made Simple: Essential Steps for Accountability and Transparency

Processing of personal data is a major element of any company. The process is automated to improve processes, contact employees and clients, and analyze data from the past.

To ensure compliance with GDPR, you need to keep records of all processes. This article will guide you in creating your internal file so that you can prove your accountability to the supervisory authorities.

Data Mapping and Inventory

Being able to have a comprehensive, detailed overview of your personal information can be crucial for the transparency of your organization and to ensure accountability. This is also the most effective way to assess if your organization is legally able to the processing of personal data.

The process of mapping data is a complex undertaking that often it involves multiple departments in the organization (marketing as well as web development, HR, etc.). It is essential to locate an expert who can assist create this mapping with ease and precision in addition to supporting the variety of personal data you need to use in your business processes.

A complete and accurate database map is the very first stage in the implementation of an internal accountability mechanism required by Article 30 of GDPR. This will help you complete requests to view and erase personal information within a reasonable timeframe as well as demonstrating the honesty and thoroughness that the legislation on privacy requires.

Purpose of Data Processing

One of the primary reasons for privacy laws is to ensure transparency and accountability to data processing. This is, however, difficult to achieve without a detailed record of the types of data taken, the reason for it, and where and when.

It’s the reason Article 30 of GDPR requires organisations to keep records of and an overview of personal data processing activities and to make them available upon an inquiry from supervisory authorities. This document also includes types of data used, the recipients, the purpose for processing and a description of the security measures currently in use.

The initial compilation and ongoing monitoring of RoPA can be time consuming. It can take up a lot of resources, particularly when large corporations process lots of various types of personal information. It is nevertheless essential in self-auditing, and for identifying any weaknesses or areas to enhance and enhance the efficiency of methods.

Data Categories and Types

The GDPR demands that companies who use personal data to maintain detailed records of danh gia tac dong xu ly du lieu ca nhan their processing procedures, referred to as a document of processing activities (RoPA). They must be available to authorities upon request.

Practically, the only way to create a RoPA that’s meaningful and valuable is to break down the business processes into segments that are consistent in terms regarding the kinds of data that is processed in the respective areas. These could be business-related functions like HR, sales and marketing or it might involve geographic locations, such as a warehouse or manufacturing facility.

Then, consider which lawful bases you employ to handle every set of data. This will help you differentiate among data sets to ensure that you can respond to access requests from individuals who are data subjects.

Data Flow Analysis

Data flow analysis is the process to document the origin data, locations, and sources of personal data in the organization. Similar to Data Protection Impact Assessment (DPIA) but they are used for distinct functions and purposes.

An analysis of the flow of data at a granular level aids in the preparation of records of processing activities, which are a requirement for many organizations under GDPR Article 30, and is a best practice for all of them. The records must include information of the purpose of processing, the legal basis, the status of consent, as well as transfer across borders.

Furthermore, a detailed data flow analysis could reveal ways to improve constant folding, as well as other strategies for optimizing data and find potential problems. Additionally, it’s an essential tool in incident response and management. When, for instance, an incident of security occurs and data flow analysis is required, it can rapidly determine what data is affected and what measures to take.

Data Subjects and Consent

Data Subjects are individuals about whom personal information is stored. They have a number of rights, including having the right of access to their data and rights to have it deleted or corrected.

Consent is among the legitimate bases for processing personal data. It must be given freely and in a specific way. Also, consent should be clearly stated and lucid. The consent must be clear and shouldn’t be an automatic option for anyone who provides an email address or ticks a box on a form.

If a user of your data refuses or withdraws consent you must stop using your personal information (unless an alternative legal reason is in place). The data subject must be kept in a file of your decision, as well as any withdrawals of consent. You must also inform them of any other legitimate grounds to process their personal data.

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