Finding the balance between data control and data sharing

Sharing is caring; isn’t that what we’re taught from a young age? Sharing is part of the foundations of human social development. However, as adults, we do not want to share everything, especially when it comes to our personal data. When we read that data sharing is a business imperative for organizations, we think of sharing a bit differently. 

The digital transformation accelerated by the pandemic highlighted the benefits of large-scale data sharing to boost innovation; however, data sharing projects in enterprises are still struggling to emerge. 

Organizations shouldn’t be torn between the return on investment and the ability to ensure proper and necessary control when discussing data projects. Data control and compliance are key to mitigating risk across an increasingly complex cloud and hybrid landscape. And data sharing is crucial to ensure data is available to anyone who needs and should have access to it to drive business outcomes.

What does the public sector have to say? 

It was not until recently that governments started taking charge of technology issues. Today, technology and data are top-of-mind for most political agendas. This turn of events coincides with the emergence of Web 2.0 and social media platforms, where users unknowingly began a new society within our society and had to adopt new legal, ethical, and moral rules. 

The General Data Protection Regulation (GDPR) introduced a new turn in the digital world. The European Union opened the way to a more responsible and transparent data industry. To this end, new initiatives and proposals are emerging across the globe. We are starting to see the same trend in the U.S. For example, California’s Consumer Privacy Act (CCPA) seeks to protect the personal data collected by businesses and punishes companies for exposing such data. Massachusetts is also adopting stricter consumer-privacy laws with The Massachusetts Information Privacy and Security Act (MIPSA). State-by-state, more privacy policies are emerging. 

These proposals aim to provide a framework for organizing data sharing to foster innovation and collective intelligence for the good of society. The COVID-19 contact tracing applications launched in different countries illustrate this phenomenon. Citizens have access to data on the evolution of the pandemic and are encouraged to declare themselves in case of a positive test to alert people who may have been in contact. 

Serving the common interest is also the goal of the public sector’s open data initiatives. Data is made available free of charge to foster innovation. The applications are numerous, such as in transportation or urban planning. Traffic applications such as Waze use published data on road works integrated into the application to provide users with a real-time overview of road conditions. After all, sharing data has plenty of benefits. 

The growing importance of data democratization

While it’s clear that organizations in the private sector understand the value of a data sharing strategy, existing barriers make it difficult to operationalize. The problems faced are common to every data project: the technology and its deployment, trust, data control and compliance, and organizational culture. From a technology perspective, APIs are the foundation upon which every successful data sharing strategy will be built. 

Developing APIs is the first step in implementing a data sharing strategy. Typically, this requires resources and days of developers’ time. New technologies are emerging, however, to simplify the process. For example, data analysts can use solutions that provide standard API libraries that provide access to the information needed within an hour of publishing an API. Access is managed automatically from the tool. 

To gain an ROI from data sharing, the data must be governed and trustworthy. Ensuring data quality is a challenge for 50% of organizations. Data quality has to be monitored consistently and leaders need to define who can access what data. All of this is part of the data control and compliance cycle. 

A good example of doing this well is the retail industry. Many retail organizations have created centralized data sharing systems, with encrypted and anonymized data, made accessible securely on-prem or in the cloud. This allows industry leaders to create effective customer experiences. 

For example, Office Depot Europe had a wide range of customer and product data stored across a range of locations and applications. The siloed data made it really hard to understand where data came from or how to use it for business decisions. By implementing data sharing solutions, they were able to standardize data processes and saw a 40% improvement in data integration velocity. This led to faster customer decision-making and major cost savings.

These data-driven wins emphasize the importance of a culture of data throughout an organization. 

Today, data sharing projects are mainly driven by business departments — marketing, sales, or finance — while IT provides a security framework and technological levers. But business units still need to understand each other and eliminate data silos. As data sharing becomes a matter of course for many organizations and new projects, the ultimate success of such will depend on the transparency of the data shared with customers and users — and a common understanding of what that data means. 

Felipe Henao Brand is senior product manager of Talend.