• Shawn Roger, Senior Director of Analytic Strategy at TIBCO Software


• 27.07.2018 08:45 am
undisclosed

It’s been a long time coming, but General Data Protection Regulation (GDPR) is finally here, ready to bring to fruition the most seismic change to data management and security in recent years.  

Depending on the mindset, investment and level of digital sophistication that exists within an organisation, it’s a deadline that has sparked varying responses from those having to negotiate the myriad of complex reforms around the storing and processing and utilisation of EU citizens’ data.

For businesses caught napping, with rudimentary systems ill-equipped to deliver the heighted privacy and protection demanded, it’s likely to be trepidation and reactive panic. By contrast, those with a mature digital infrastructure in place and who recognised the wider opportunity that exists beyond box ticking compliance, this signifies the official start of a new era in data management as they align legislative adherence to their broader digital strategy.

In essence, GDPR demands greater transparency and accountability around data processing, and those that successfully deliver on this front will make huge systemic improvements to their entire approach to analytics and data science. As a result, they will generate deeper actionable insight and improved ways of working, leading to faster times to market and ultimately, an improved customer experience.

‘The Right to an Explanation’ rule is a case in point. As the name succinctly says, this enables the consumer to discover exactly what drove an automated decision process to determine a mortgage refusal, a hike in insurance premium or even the dismissal of a particular job application. In this context, automated decisions have never been more accountable. Any bias - be it on age, gender or race - that can creep into machines trained by human programmers, will be quickly unearthed, with heavy financial penalties looming for those who fall short.

A significant positive of this, is the promotion of a more ethical and mindful decision-making data culture, which starts by ensuring transparent procedures and practices permeate an organisation’s DNA.  Creating an environment where a collective understanding of the algorithmic models used and subsequent outcomes will prevail, rather than it being the sole domain of a chosen few. This means a collaborative approach to data management and a shift away from scenarios in which data scientists work in siloes, divorced from other stakeholders and the rest of business relying on opaque techniques that can be difficult to explain and interpret.

To make this a reality, businesses need to embrace the kind of enterprise tools and frameworks that optimise data visibility and make data discovery as intuitive and accessible as possible, with more speed and less complexity. The ability to cut through the swathes of intelligence to home in on areas of high risk and opportunities becomes the game changer. Undoubtedly, data virtualisation technology is a core weapon in an enterprise’s arsenal, not only in enabling immediate access to more datasets, but by integrating disparate data sources in real-time.

Furthermore, this new era of heightened regulatory adherence underlines the criticality of eliminating human error and the growing significance of automation in analytics to do the heavy lifting and take out some of the guess work.  Companies now need to invest in machine learning-driven, AI-powered applications with features that increase accuracy by automatically correlating and recommending related data sources to enhance the analysis and insight. Why? For one, they are simply far better equipped to handle the governance and constraints that GDPR presents.

It is this level of sophistication that becomes a vital ingredient when addressing another core component of the legislation - the Right to be Forgotten – which allows individuals to request the deletion of all their data held by an organisation. Eradicating all mention of a customer’s existence from a company’s diverse data landscape is a task that can easily catch out those who underestimate the enormity of the task.

As with all aspects of the GDPR, doing your best simply won’t cut it – only 100% execution will suffice, a demand that will force all players to up their data game for the greater good of the enterprise.