Will GDPR Be the Death of Big Data?

The Law of Unintended Consequences says there are unforeseen, unintended outcomes to purposeful actions. Companies working in Europe are about to get a lesson in that when the General Data Protection Regulation (GDPR) goes into effect in May 2018.

GDPR brings tough new rules mandating data handling, transparency, highly regulated usage policies, and consumer-friendly privacy terms for EU citizens. Any company that wants to do business with European residents will need to comply with GDPR or face stiff financial penalties.

Since it hasn’t gone into effect yet, we don't know all of the unintended effects, but one can be seen coming a way off: the impact of GDPR on big data and analytics projects.

GDPR is different from American regulations in that it is overarching of all industries, whereas in the US, regulation of content and data varies from one industry to the next. Health care and banking are subject to very strict rules, while retail is more freewheeling.

GDPR gives European consumers the power to control how their individual data is gathered and used. More important, it gives them the right to demand changes to their data, including removal. In big data scenarios, companies are used to doing whatever they want with the data they collect and rarely go back and make changes.

So, can you imagine the chaos, not to mention demand on resources, when Europeans start demanding changes or removal of their information from data stores?

Also, companies must be able to assess whether the data is being used in a manner that has consent from the owner and is acquired in the proper way. Companies will no longer be able to collect data from people for one reason, and then use it for a different reason. A company cannot collect sales information and then use it to predict future buying patterns, for example.

GDPR gives European citizens incredible influence and control over their personal data, and it puts short time limits and answering their requests, so you need to know where that data is quickly. GDPR gives citizens:

If you are running real-time analytics, do you really want to have to drop everything and answer these requests? Well, you will. But if all teams are aligned with GDPR compliance, you can minimize the pain of consumer requests. Communication between teams is key here, and inter-office communication in some companies is notoriously bad. Perhaps those EU fines will motivate your people.

In a white paper entitled "Five Essential Pillars of Big Data GDPR Compliance," data science platform developer Dataiku argues that GDPR doesn't mean the end of data science, but companies will have to develop a more controlled method of data collection so they don’t get in trouble with the new regulations.

The changes in GDPR will certainly require shifts in organizational structure and processes, most notably staffing, says Dataiku. New data governance rules will have to be implemented across the entire company, from IT to marketing to customer support.

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Organizations will need to take stock of where all data is stored and ensure that it is accessible to make request changes. Data team leaders should be able to easily understand and audit data sources, who has access to what, and what sources are being used for which projects.

This means keeping all of the data in a single, centralized store, and big data doesn't work that way. It frequently keeps multiple data stores from multiple sources. You don't have to change your data storage methods with GDPR but it sure will be a lot easier if everything is in one place.

In a way, GDPR might force you to clean up your data. Rather than just blindly sucking up everything and filling your data lakes, you will be forced to practice "good data hygiene," as it were. In the end, if you know your data better to comply with the overtly intrusive nature of GDPR -- and let's face it, it really does stick its nose way into your business -- you will have better data to work with.

GDPR means the end of anything-goes data collection, but it doesn't have to mean the end of data gathering and analytics. If done right, it could result in better analytics as you keep your data clean and relevant.

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— Andy Patrizio has been a technology journalist for more than 20 years and remembers back when Internet access was only available through his college mainframe. He has written for InformationWeek, Byte, Dr. Dobb's Journal, eWeek, Computerworld and Network World.