Click to learn more about author Dean Gonsowski.
We’re in the midst of the Fourth Industrial Revolution. This revolution, also referred to as 4IR or Industry 4.0, is changing how we live, work, and relate to each other. According to Bernard Marr, a strategic technology advisor, this revolution “represents the combination of cyber-physical systems, the Internet of Things, and the Internet of Systems.”
In a 2016 article, Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, wrote:
“When compared with previous industrial revolutions, the Fourth is evolving at an exponential rather than a linear pace. Moreover, it is disrupting almost every industry in every country. And the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance.”
With digital transformation happening at breakneck speed, companies are creating and collecting more data than ever to accelerate their operational efficiencies and company growth.
More Data, More Management
As technologies such as GPS, AI, and blockchain become increasingly prevalent in our lives, consumer expectations are also changing rapidly. A global study from Salesforce found that customer trust is increasingly important, which, when combined with the increased proliferation of data privacy laws, is putting immense pressure on companies to secure and protect the massive amounts of personal data they collect daily.
The vast amount of data available today is both a risk and a liability. While consumers are still happy to hand over personal information for personalized experiences, they also want reassurance that their data is being handled with care. Salesforce CEO Marc Benioff calls this potential exchange a “crisis of trust.”
Consumers are starting to ask more questions about how their data is being handled — from how it’s collected to where it’s stored and for how long. Privacy laws such as the California Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR) have given consumers several rights over their data, including the right to erasure, data portability, and rectification. According to Gartner, “Unlike many regulatory standards, modern privacy laws demand a fundamental transformation in how personal data is managed and cannot be dismissed with a narrow checkbox mentality.”
With privacy obligations increasing, an organization’s inherent bias to keep and process everything is proving to be an increasingly risky practice. According to a report by PwC, only 51 percent of private-sector companies have an accurate inventory of where personal data for employees or consumers is collected and stored. Understanding how data moves through your organization is a requirement to being able to secure and protect it — after all — how can you manage what you don’t know you have?
Automated Data Mapping
Protecting personal information is hard. It’s spread out across numerous, often unknown, databases, repositories, and environments.
Data mapping is the starting point for any cyber and privacy framework implementation. It helps provide organizations with an accurate picture of what data they hold, where it is located, when it’s transferred, and who has access to it. The sheer volume of information flowing throughout an enterprise makes manual data mapping — the process of discovering and classifying data — incredibly difficult, not to mention time-consuming and potentially fraught with error.
Like bloatware led to SaaS, the non-stop proliferation of data creation has led to the creation of a new category: Data Mapping as a Service or “DMaaS.” Data mapping exercises have been attempted for decades but were always fraught with instant obsolescence since they were based upon snapshots in time and custodian interviews. DMaaS transforms the way data professionals manage their data universe with automated, always-on, actionable data mapping.
Protect and Manage Your Data
Discovering, classifying, and protecting data is no small undertaking, but with privacy a growing competitive differentiator, automation can help to lighten the burden. A data mapping exercise is not a “one-off” activity. A data map needs to be evergreen and accurate to ensure compliance with regulations such as Article 30 of the GDPR, which requires that “every data controller and data processor is required to keep a record of their processing activities, including the purpose, a description of the data subjects’ categories, information about whether personal data was transferred to a third party, and details of any appropriate data safeguards in place.”
Data privacy goes hand-in-hand with security, and it all starts by understanding the full extent of your data universe, facilitated by a data map. There are significant business benefits to investing in data privacy, including lower losses from data breaches, operational efficiencies, and consumer trust.
SaaS is the natural evolution of software. DMaaS is the natural evolution of data mapping.