The Enlightening Side of GDPR Compliance
If the upcoming General Data Protection Regulation (GDPR) is like most government mandates, the thinking goes, it will be a tax on business and a hindrance to productivity. But if you take the right approach, some experts say, the GDPR could actually be a boon to analytics.
By now you’re probably aware that in just 38 days, the European Union begins enforcing GDPR, which was passed two years ago to harmonize a hodge-podge of privacy laws across Europe. The new regulation was designed to, among other things, give EU citizens control over their personal data by imposing stiff penalties for any organizations that use their personal data without consent. It also requires organizations to take certain measures to protect citizens’ personal data, which will (hopefully) reduce the severity and impact of major data breaches.
The law protects the data of 740 million Europeans, more than 10% of the Earth’s population. In other words, when it comes to big global corporations that sell goods and services around the planet, the days of playing fast and loose with peoples’ data are over. While we don’t have an American version of the GDPR (at least not yet), essentially the gig is up for the Wild West days of “anything goes” in the analytics arena.
In that regard, the GDPR is a significant wakeup call for organizations to mature their data management and analytic practices – and to do so quickly. While no corporate leader likes being ordered how to run her company, the prospect of losing up to 4% of annual revenue per GDPR violation provides a compelling incentive to accelerate data management initiatives.
The new regulation is also a boon for software companies that have the experience in building the types of consent-management systems that GDPR requires. The folks at MarkLogic, which develops a multi-model database management system, have been busy with GDPR remediation engagements and have noticed some patterns emerging from the work.
David Gorbet, SVP Engineering for MarkLogic, says GDPR finally caught up with people. “For a long time, they were unprepared,” he tells Datanami. “They didn’t underhand how it impacted them. They thought it was a Europe-only thing. A lot of people didn’t know how to get started.”
GDPR represents a very complex set of requirements that are vastly different from other regulations that impact the collection, storage, and use of data, such as HIPAA or PCI DSS, according to Gorbet: You can’t prove compliance by generating the correct reports. “It’s not a reporting regulation,” he says. “It’s an operationalization regulation. It’s about how you change your operation in order to be compliant with GDPR.”
That makes things tougher, to say the least. Being GDPR compliant requires an organization to understand where all their data resides and what it’s used for, Gorbet says. Then they need to relate that data to potentially millions of individuals, and then create consent management systems to control access to that data. “That’s a lot trickier than a typical compliance operation,” he says.
Over the years MarkLogic’s professional services arm has developed many of these types of consent management systems. It’s software manages consents for big publishing houses that need to understand which customers have legal authority to specific songs and movies. The system helps answer questions like, Is this iTunes consumer entitled to play this song, or is this the director’s commentary for this boxed set of Stephen Spielberg movies entitled to be distributed in this particular region?
Gorbet points out that consent management was also a big part of MarkLogic’s involvement in the development of Healthcare.gov, the much-maligned Obamacare website. Specifically, the MarkLogic database was used to create a Data Services Hub that reached out to databases hosted by the IRS, the Social Security Administration, and others to see whether or not a given citizen is eligible for a specific insurance program.
This is the sort of consent system that every large organization will ultimately need to comply with GDPR, Gorbet says, but building it is not easy. In some cases, customers will move all the relevant data into MarkLogic’s NoSQL database, which features a flexible schema. In other cases, a MarkLogic system will create a virtual layer controlling access to data that lives in other physical data stores, which could include relational databases, Hadoop file stores, object file systems, and mainframe flat files.
Staying on top of what people consent an organization to use their data for and what they do not is also a big challenge. “With GDPR, organizations can ask for consent at whatever level they want… and GDPR allows you to revoke them any time,” Gorbet says. “It’s not just a Boolean yes or no. It can be quite a complex thing.”
So for instance, a customer may give an organization the okay to use his email address to contact him about a certain product, concern, or event, but not allow the organization to use his phone number for them. This personally identifiable information (PII) is some of the most sensitive data that an organization stores on behalf of its customers, but it’s also some of the most valuable data, from an analytics perspective.
According to Gorbet, that level of complexity surrounding the individual permissions in a GDPR project actually jibes well with the capabilities of graph or semantic database, which is one of MarkLogic’s modalities. “Semantic is a great way to traverse that graph, to figure out if a particular entity [is entitled to something],” he says. “Performance is faster. Traceability is better. But in order to apply your policy to the data, you may want to apply it through a ontology.”
GDPR is forcing organizations to get smart about how they store PII data in order to protect the privacy of individuals. But that work also brings side benefits to the organization in the form of better organized data and a finer-grained view of their customers, too.
“Now for the first time ever, they can understand their exposure to a particular individual, which is a really big business benefit,” Gorbet says. “With a data hub they don’t have to [repeat the process]. Subsequent use cases are actually cheaper because the data is all in one place.”
The better organizations are at adhering to the new requirements under GDPR, the better organized their customer data will be, and the more analytical options will open up to them, Gorbet says.
“The smart companies are not seeing GDPR as a tax that they have to pay,” he says. “They’re seeing it as a reason to finally build that customer 360 view that they always wanted.”
October 23, 2020
- GoodData Adds Enhanced Self-Service Tools to Drive Business Intelligence Adoption
- IBM and R3 Collaborate to Expand Blockchain Capabilities and Services Across Hybrid Cloud
- Amperity and Zendesk to Help Brands Offer Customer Personalization
- Quantum Tape Systems Safeguard Scientific Data for British Antarctic Survey
October 22, 2020
- Minitab Launches Launches New Solutions to Help Organizations Accelerate Digital Transformation
- AccuWeather Sponsors Climate Change Machine Learning Research Competition at University of Toronto
- Precisely Delivers First End-to-End Data Integrity Suite for Confident Business Decisions
- Centerity Recognized for Market-Leading AIOps Platform with Integrated Cyber Security
- Protegrity Unveils Vision for the Secure AI Era
- Qlik Acquires Blendr.io to Drive Real-time Data into SaaS Applications and Automate Enterprise Processes
October 21, 2020
- The AA Executes Hybrid Cloud Strategy for Data Analytics with Actian’s Avalanche Cloud Data Warehouse
- Exasol and Nuqleous Join Up to Bring Data Analytics to Retail and Consumer Product Companies
- InterSystems Partners with AtScale on New Adaptive Analytics Within IRIS Data Platform
- YottaDB Announces Octo 1.0, a Plugin for Using SQL to Query Data
- Anyscale Announces $40M in Series B Funding Led by NEA
- KIOXIA America to Showcase Next-Gen SSDs at Dell Technologies World
- Medallia Partners with Tableau to Help Companies Visualize Customer Experience Data
- Enterprise Strategy Group Finds Massive Cost and ROI Benefits from Yellowbrick Data Warehouse
- Machine Learning Capabilities Come to the Majority of Open Source Databases with MindsDB AI-Tables
October 20, 2020
Most Read Features
- Big Data File Formats Demystified
- Systemic Data Errors Still Plague Presidential Polling
- Do You Need a Chief Data Scientist?
- Data Culture ‘Disconnect’ Identified in New Index
- How to Build a Better Machine Learning Pipeline
- VC Ben Horowitz Dishes on Hadoop, AI, and Data Culture
- How Geospatial Data Drives Insight for Bloomberg Users
- Is Python Strangling R to Death?
- 10 Big Data Statistics That Will Blow Your Mind
- Understanding Your Options for Stream Processing Frameworks
- More Features…
Most Read News In Brief
- Qubole is Latest Acquisition Target
- Testing Data Literacy on Main Street
- Informatica Likes Its Chances in the Cloud
- Pandemic Driving ‘Back to Basics’ in Big Data, Study Suggests
- TigerGraph Offers Free Graph Database for On-Prem Analysis
- Palantir Looks to Build on Snowflake’s IPO Success
- AI Startup Uses FPGAs to Speed Training, Inference
- Patchwork of Data Privacy Laws Sows Confusion
- War Unfolding for Control of Elasticsearch
- New AI Tool Maps the Families of the Bible, A Song of Ice and Fire
- More News In Brief…
Most Read This Just In
- Datanami Reveals Winners of Fifth Annual Readers’ and Editors’ Choice Awards
- Tableau Launches Free Data Literacy Training Program
- NASA, ICIJ, ATPCO, Lyft and More Choose Neo4j for their Knowledge Graphs
- Hazelcast to Provide Additional Capabilities to IBM Cloud Pak for Multicloud Management
- Fujitsu Enters Strategic Alliance with Palantir Technologies
- Collibra Launches New Partner Program
- KNIME and H2O.ai Accelerate and Simplify End-to-end Data Science Automation
- Data Science Professor Receives $1.25 Million Grant from Department of Defense
- Alida Integrates Stratifyd AI-powered Analytics Engine into New CXM Platform
- Google Cloud Unveils AI and Machine Learning Privacy Commitment
- More This Just In…