3 ways businesses can build more resilient data architectures

Data sharing is a central element of the digital transformation that companies have experienced over the years. According to Chief Data Officers (CDOs), the ability of companies to create resilient, privacy-focused and shareable data architectures directly affects their growth prospects.

The Gartner survey trends and forecasts for CDOs predict that by 2023, organizations promoting data sharing will outperform their peers on most business value metrics. At the same time, however, Gartner predicts that by 2022, less than 5% of data-sharing programs will be able to accurately identify reliable data and find reliable data sources.

It is difficult to build a resilient data architecture. In terms of privacy, signal loss is the top challenge to build a successful system. Breaking down data silos and merging abundant data into one universal snapshot of proprietary data has made processing and activating data equally challenging.

Data sharing between teams is central to successful digital acceleration, and there are three main ways businesses can move toward building more resilient data architectures:

1.) Focus on your team

The strength of any building or bridge depends on the team of architects and planners involved in its construction. The same principle holds true in the field of data architecture. As businesses build and refine their data architecture, take a closer look at how engineers, data scientists, legal and privacy experts, and project managers are equipped for the job.

Ensure that teams have the appropriate training and certifications to address knowledge deficiencies, especially in the area of ​​privacy. Ask team members to be certified by a major professional body such as the International Association of Privacy Professionals (IAPP). These organizations offer courses and certifications for a variety of roles, so that each team member can learn about data privacy requirements in a way that is specific to their job. Investing in privacy knowledge across the board can eliminate this misconception.

After investing in training, encourage collaboration between all data team experts and ensure that the project is given ample time to promote collaboration. Sealed teams do not work together efficiently. Sometimes, teams rushing to bring something to market in a non-compliant manner can result in a complete rebuilding effort that takes more time, effort and money to fix.

Teams need time to understand the regulatory space, work together to create data architectures tailored to rules and privacy implications, and to create a more resilient system. Teams that work together and have strong relationships internally often bridge the knowledge gap and create architectures that better serve the end user.

This collaboration can also create hybrid roles where team members share privacy as a secondary skill. Many organizations employ privacy experts in data teams, but consider how information-sharing roles, such as sales or marketing, can benefit from better shared privacy knowledge. Optimize team structures to introduce more hybridized data and privacy roles to break the silos that make data architectures ineffective.

Just as data should not be a sealed asset, privacy should not be a sealed liability. Organizations are evolving to respond to this shift.

2.) Make compliance your first mission

Compliance should be integrated into any new project from the beginning, so it is important to align with this team at the beginning of any project. With a collaborative, trained team, each member’s first step should be to devote time to understanding privacy considerations and potential risk areas in order to be able to create a consistent structure.

It takes extra time and effort to do this step first, but it does ensure that the project will be built for the first time. Trial and error is not the best approach to privacy-focused challenges in data architecture. Fixing inconsistent structures can cost you more money and time in the long run.

3.) Work from a source of truth

As the governance, risk and compliance landscape has become increasingly complex over the past decade, companies are slowly realizing that they can no longer rely on a single system or architecture to orchestrate data. Global organizations are required to adhere to a number of rules (GDPR, CCPA, IPPA and more) and the noise between these constantly changing requirements is too complex for a stable system. These organizations obtain data from many sources and then work to obtain, store and analyze data in parallel data warehouses. Multiple inputs and outputs compromise compliance and privacy goals.

To ensure greater resilience, companies need to create and implement a basic logic for storing and securing data – the only source of privacy data that certifies that user privacy is intact. Elastic architecture has the power to show that whatever happens with data, user privacy is respected in every system.

Big Data is losing its grip on architecture, paving the way for a privacy-focused approach. In the midst of this paradigm shift towards tighter compliance, the organization is facing challenges. Tightening the structure with internally and externally integrated data channels in a team to increase resilience and meet the challenges that all companies need to solve in their data architecture.

Julian Llorente is the director of product and data privacy at Tealium,


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