Data exchange is a central element of the digital transformation that companies have experienced in recent years. According to Chief Data Officers (CDOs), organizations’ ability to build resilient, privacy-centric, and shareable data architecture directly impacts their growth potential.
Trends and predictions from a Gartner survey of CDOs predict that by 2023, organizations driving data sharing will outperform their peers on most business value metrics. At the same time, Gartner predicts that by 2022, fewer than 5% of data sharing programs will correctly identify trusted data and find trusted data sources.
A resilient data architecture is difficult to build. From a privacy perspective, signal loss is one of the biggest challenges in building a successful system. Breaking down data silos and merging a plethora of data into a universal snapshot of one’s data has made data processing and activation just as challenging.
Data sharing between teams is central to successful digital acceleration, and there are three main ways organizations can take steps to build a more resilient data architecture:
1.) Focus on your team
The robustness of a building or bridge depends on the team of architects and designers involved in its construction. The same principle applies to data architecture. As organizations build and refine their data architecture, it’s important to take a close look at how engineers, data scientists, legal and privacy professionals, and project managers are equipped for the job.
Ensure teams have the right training and certifications to fill knowledge gaps, especially around privacy. Encourage team members to get certified by a major professional body like the International Association of Privacy Professionals (IAPP). These organizations offer courses and certifications for a variety of roles, allowing each team member to learn privacy requirements in a way specific to their job. This can clear up misunderstandings while investing in data protection knowledge across the board.
After investing in training, encourage collaboration between all experts on the data team and ensure projects are given sufficient time to foster collaboration. Isolated teams don’t work together efficiently. Sometimes, teams rushing to get something to market in a non-compliant manner can result in a complete rebuild that takes even more time, effort, and money to fix.
It takes time for teams to understand a regulatory space, structure data architecture to conform to rules and privacy implications, and work together to build a more resilient system. Teams that work together and maintain strong relationships internally are more likely to bridge knowledge gaps and create an architecture that better serves the end user.
This collaboration can even lead to the creation of hybrid roles where team members share data protection as a secondary expertise. Many organizations have privacy professionals working on data teams, but consider how data-informed roles like sales or marketing could benefit from more shared privacy knowledge. Adjust team structures to embrace more hybridized data and privacy roles to break down the silos that render data architecture ineffective.
Just as data should not be an isolated asset, data protection should not be an isolated responsibility. Organizations are evolving to respond to this change.
2.) Make compliance your first mission
Compliance should be built into any new project from the start, so it’s important to coordinate with this team from the start. With a collaborative, trained team, each member’s first step should be to take the time to understand privacy considerations and potential risk areas in order to build a compliant structure.
It takes extra time and effort to do this step first, but it ensures the project builds right the first time. Trial and error is not the best approach to privacy-centric data architecture challenges. The subsequent correction of non-compliant structures costs more money and time in the long run.
3.) Work from a single source of truth
As the governance, risk, and compliance landscape has grown exponentially more complex over the past decade, organizations have begun to realize that they can no longer rely on one system or architecture to orchestrate data. Global organizations must comply with many regulations (GDPR, CCPA, IPPA and more), and the nuances between these ever-changing requirements are too complex for a static system. These organizations receive data from many sources and then do the work of retrieving, storing, and analyzing the data through parallel data warehouses. Multiple inputs and outputs confuse compliance and privacy goals.
To ensure greater resiliency, organizations must create and enforce a basic logic for storing and securing data – a single source of privacy data that confirms user privacy is intact. A resilient architecture can demonstrate that user privacy is respected in any system, whatever happens to data.
Big data loses architecture and makes way for a privacy-centric approach. A company can face challenges amidst this paradigm shift towards stricter compliance. Streamline structure internally within a team and externally with unified data channels to build resiliency and address the challenges all organizations seek to solve in their data architecture.
Julian Llorente is Director of Product and Privacy at Tealium.
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