Does data governance guarantee the protection of personal data?
It sounds like a trick question. And, in part, it is.
In recent years, personal data protection stopped being a purely legal matter. Today it is a concern that runs across the whole organization. Even so, many companies are still stuck on a much more basic problem: they don't clearly know what data they hold, where it is, who uses it or what for.
That is where the idea of data governance comes in. But before getting there, it helps to understand something simpler.
Let's start with something more familiar: managing data
Organizations have always had data. For a long time it was seen as a byproduct of operations:
If a company sold something, customer data appeared.
If it charged for it, payment data appeared.
If it ran marketing, contact data appeared.
The problem is that this data wasn't treated as something valuable. It sat scattered, duplicated, with no clear control. In other words, it was there, but nobody was managing it.
As technology and storage and computing capacity grew, data started to be seen as an asset. And that is how data management spread.
Managing data means, in simple terms, deciding (it no longer happens by chance) what to collect and process, and how to use data safely and efficiently to get better results. It isn't an end in itself. It is a tool for reaching other goals.
If a company wants to grow a product, it will need quality data to understand its customers, make decisions and measure results. If it wants to improve the experience, it will need customer feedback data, resolution rates, channel interactions, and so on. Data management exists to support the company's goal and its strategy.
So what is data governance?
If data management is the day-to-day execution, data governance is the framework that puts that execution in order.
Data governance sets the rules of the game. It establishes who is responsible for the data, what standards it has to meet, how it is accessed, under what conditions it is used and what controls have to exist.
In practice, it lets data management happen consistently, safely and in line with the organization's goals. Without that framework, each team ends up handling data its own way, and the result is usually disorder, duplication and a lack of control.
And where does personal data protection fit in?
Under personal data protection laws, this kind of information has to be processed and safeguarded in a certain way. To do that, an organization needs to know, among other things, what personal data it holds, what it uses it for, on what basis it processes it, who accesses it and how it protects it.
That seems obvious, but in practice it doesn't always happen. Often the problem isn't a lack of intent to comply with the law. The problem is more basic: the company runs on disorganized data and, for that same reason, has no real tools to apply the legal requirements properly.
That is where data governance plays a key role. It helps identify who is responsible, classify the data, define rules for use, storage and retention, set controls and organize all of it systematically.
You can see it just by asking yourself which scenario makes it easier to protect data.
In scenario 2, there are people responsible and policies that keep good management in place over time:
Having data governance does not, on its own, guarantee the protection of personal data. It can help a great deal, but it isn't enough.
If privacy isn't part of the organization's strategy, data governance can end up focused only on organizing, exploiting or extracting value from information, without necessarily prioritizing its protection (remember that data management and governance are there to support business goals).
When privacy is built in as a principle of the organization, on the other hand, data governance becomes a natural vehicle for putting it into practice.
Getting concrete: which data governance practices help protect privacy
The short answer: practically all of them. But some are especially useful to start with.
Data catalog. It isn't the same as a record of processing activities (RAT), although the two complement each other. The data catalog brings together key information about every piece of data that matters to the organization. It lets you understand what that data means, how critical it is, who administers it, what quality rules it has to meet, how it is classified (for example, whether or not it counts as personal or sensitive data) and any other metadata the organization considers relevant.
A simple example (data catalogs can be as complex as you want):
Define who is responsible for data: data is so varied and so specific that no single person can know every set of information in an organization in depth. That is why roles are assigned.
The Data Owner usually holds the decision-making role. They are responsible for a given set of data, such as customer data. They define quality, use and security criteria, and they need to understand whether that data calls for special safeguards, for example because it is personal or sensitive data.
The Data Steward has a more operational role. They support the Data Owner in the day-to-day application of the policies and standards that have been defined. They make sure, for example, that data is properly classified, documented and managed.
The Data Custodian, by contrast, has a more technical focus. This is the person who implements the controls needed to ensure the availability, security and backup of the data.
Define data policies. Their job is to make the organization's rules for using data clear. These policies should expressly include personal data protection and information security criteria, so there is no ambiguity about what can be done, what can't be done and what the consequences of non-compliance are.
At bottom, bringing in data governance means creating the conditions, practices and role structure that make it easier to protect personal data.
