As the data privacy landscape expands, businesses employ data mapping, risk-based searches, and automated consent management to secure data privacy. However, data privacy compliance isn’t a single “one-and-done” event. The world generates 2.5 quintillion bytes of data per day. And, each day, that data undergoes ETL transformations before being transferred to DBMS (data management systems), with the hope that it can be analyzed to gain deep insights into consumer behavior.

Data is critical for informed decision-making; thus, data collection is of key importance to businesses. Meanwhile, legislative bodies continue to pass more data privacy laws to protect consumers.

A looming uncertainty surrounds data privacy compliance, however, and unless businesses tackle data privacy holistically, they risk regulatory non-compliance. Of the more than 3,200 security professionals interviewed for Cisco’s 2019 Data Privacy Benchmark study, only 59% maintained that their companies were meeting all or most of the GDPR requirements.

In light of the challenges, many organizations seek a one-time/single-use data privacy solution. They aim to mitigate their data privacy challenges in one fell swoop. However, such a scenario isn’t possible.

Here’s the problem: data privacy doesn’t really work that way. Because laws like the GDPR are constantly evolving, a one-time effort to restrict database queries isn’t sufficient. Instead, companies must recalibrate their entire approach to data governance. To secure data privacy, data classification and handling policies must be reviewed at a regular cadence.

In essence, data privacy compliance is a continuous discipline.

Data Privacy Compliance Isn’t a One-and-Done Event

Data extraction, mapping, and migration aren’t one-time events. It’s like a virus scanner; for it to be successful you need to leverage it at a regular interval. You need consistency to ensure compliance with an avalanche of new privacy laws. In fact, the reason data mapping is such a powerful solution is that it can be automated for efficiency. Reporting in Excel or running a once-a-month mapping solution isn’t sufficient. Data is growing at an alarming rate. By and large, the world’s data is expected to balloon up to 175 zettabytes by 2025, at a compounded annual growth rate of 61%.

Every new bit of data is a liability. Even when we’re talking about use-case data (how data is used to accomplish a particular business goal), fresh batches of data are being streamed every second.

There’s another side to this story: dark data. This is all of the data you aren’t actually utilizing. Mapping this type of data (especially in unstructured lakes) is incredibly difficult. Typically, it gets left out of the governance architecture & when using manual data mapping processes. However, we recommend including it. Data privacy regulations still apply to this type of data. And this “dark data” accounts for 55% of your data on average.

In all respects, data governance must be ongoing. Instead of focusing on ad-hoc governance and mapping, automate data mapping to apply privacy policies at scale. The result is a holistic, comprehensive, and solidified data privacy framework.

The frequency of your scan cadence can be based on:

  • The potential risk of data sources
  • How data changes
  • The type of data in each source
  • The presence of 3rd party data that may carry sensitive information

You can set up the right internal policies to regulate your scanning frequency. Of course, you can take an aggressive approach and regularly scan all databases to ensure broad compliance.

Figuring Out Your Data Privacy Framework

Earlier this year, a Microsoft blog post proclaimed that “Data privacy is about more than compliance — it’s about being a good world citizen.” And, while that may sound altruistic, it’s a valid point. Data privacy represents a cultural shift. When it comes to data privacy, the stakes are high. Customers are paying attention to how you handle data and regulators are scrutinizing every piece of data you collect.

Any negligence on your part can lead to the marginalization of your brand. In fact, consumers across the world will engage with your brand based on how well you mitigate data breaches. Subsequently, 85% of people will never do business with a brand that’s suffered a data breach.

And, although 79% of Americans are concerned about the way businesses utilize their data, 66% believe that it’s impossible to go through an average day without sharing data. They’re quite right to be concerned. Companies collect a massive amount of data daily, and between storing it in data lakes and analyzing it in analytics platforms, the pure magnitude of data is staggering. It’s easy to lose track of all that data.

However, if any data is leaked or exposed, it may put consumers at risk. Studies show that losses incurred from identity theft have increased by 15%, while the ensuing emotional toll can be equally devastating. According to studies, between 67% and 80% of consumers who experienced identity theft reported overwhelming feelings of depression, anxiety, and anger. Meanwhile, others felt violated (66%) and vulnerable (58%). Unsurprisingly, 7% considered suicide.

The bottom line is identity theft is on the rise, and it costs the average consumer over $1,000 to resolve — not to mention the hours of labor needed to do so.

Three Key Practices to Enable Data Privacy Compliance

To avoid consumer frictions, stay in the good graces of regulatory agencies, and mitigate your chances of damaging data breaches, we recommend focusing on three core preventative practices:

  • Data mapping: How does all of the data in your big data systems, structured databases, data lakes, and SaaS apps relate back to your governance policies? If you don’t know, find out. Data mapping helps you categorize and catalog your data sources for governance. There are a few ways this can happen on the backend.

At OneTrust, we take a granular approach to data governance. Our solution recognizes data at the elemental level, allowing us to go beyond mere identity-based categorization. We highly recommend data mapping that tackles a range of structured, unstructured, and semi-structured data sources. This facilitates a holistic approach to complying with privacy regulations.

  • Operations: Mapping data is the first step. But, you still need to formalize governance operations. Organizations need robust governance frameworks that support minimized data collection. Ideally, data mapping helps form the basis for across-the-board data privacy. Access, retention, and deletion all fall into the bucket of operations. Essentially, a formal privacy operational framework is needed to measure the efficacy of your data governance policies.

In addition, GDPR and CCPA require you to fulfill data subject access requests (DSAR). Mapping helps you gather the key pieces of data necessary for these transactions, while DSAR automation helps you fulfill requests within the specified timeframe stipulated by data privacy standards.

  • Infrastructure: You need technology to enable data governance. Essentially, you’ll want to use data cleansing tools and leverage solutions that enable data governance automation. Digital transformation (at least on the data privacy and security layer) is a necessity in today’s hyper-regulated data privacy ecosystem.

Establishing a Regulatory-Agnostic Data Privacy Architecture

With evolving data privacy compliance requirements and the exponential growth of data, businesses need to stop thinking about data privacy as a siloed process. Instead, data privacy governance should be baked into your IT infrastructure.

Running a few “mapping scans” or applying new policies to disparate groups of data isn’t sufficient. You’ll need to build a regulatory-agnostic framework that supports holistic, continuous data mapping and privacy operations management.

We believe that building future-proof data privacy architectures shouldn’t be difficult. Our solution helps automate data mapping at the elemental level — which facilitates speedier governance, more accurate policy control, and smarter data analysis. Are you ready to experience the future of data privacy? Contact us today. Let’s create tangible data architectures that go beyond satisfying compliance requirements to create better consumer experiences.

By Haribalan Raghupathy, Sr. Director Customer Engineering