SHARE
Facebook X Pinterest WhatsApp

The Impact of Data Sovereignty on Integration Strategy Requires a ‘Goldilocks’ Solution

thumbnail
The Impact of Data Sovereignty on Integration Strategy Requires a ‘Goldilocks’ Solution

Technology, internet, business and marketing. Young business man writing word: Data protection

Meeting data sovereignty regulations is essential for business success and requires the right data management balance between centralized control and local execution.

Jan 3, 2024

Throughout history, the handling of data has always sparked debate and prompted regulatory measures. In recent times, we have witnessed the emergence of governmental firewalls, such as the one in China, internationally applicable regulations like GDPR, and the enforcement actions taken by Meta. These developments indicate a future where the proliferation of data, coupled with the use of multiple clouds, will present significant challenges in controlling data flow to an optimal degree. Striking the right balance is crucial – excessive control hampers digital operations, while insufficient control can lead to costly data breaches.

To address this, businesses need a data management and integration strategy that combines central control and local execution. However, implementing such a strategy is easier said than done from a technical standpoint. Traditionally, organizations faced a choice between a monolithic infrastructure approach that offered centralized control but hindered agility or a fully decentralized approach like microservices that offered flexibility but lacked oversight.

Nonetheless, a solution lies in re-architecting the infrastructure to create a clear separation between the control and execution planes. This approach allows businesses to achieve the best of both worlds, finding the “Goldilocks” balance. By doing so, companies can maintain a coherent strategy while empowering individual departments to function optimally.

This re-architecting effort is driven by specific outcomes. As the international landscape for data management and regulation evolves, two primary challenges emerge for multinational data-driven organizations: jurisdictional boundaries and firewalled environments.

See also: Decoding the Customer Data Landscape: Addressing Privacy Concerns

Data jurisdictions: Regulating movement in a framework of common practice

Managing data across jurisdictional boundaries is a complex task, yet not insurmountable. Varying data regulations and their implications on data processing and storage disrupt the normal operations of international businesses. It is crucial for organizations to recognize the extent of changes required without necessarily advocating for amending existing laws. The recent data-related fine imposed on Meta serves as an example of the change that businesses must undergo. The challenge lies in designing and executing strategies that can transcend jurisdictions. A centralized control plane facilitates the design of standardized approaches, while a local runtime plane enables the execution of these centrally designed integrations and processes. This allows businesses to comply with regulations and apply local intelligence to their operations, thus delivering added value to customers, partners, and employees.

Advertisement

Firewalls: Regulating data and business continuity

Navigating data management across firewalls presents a trickier challenge. Notably, the Great Firewall of China stands out as a prominent example. When data cannot freely flow through such boundaries, coordinating operations in one of the largest markets becomes a complex endeavor. Nevertheless, a central control plane can still design integrations and processes that are deployable locally without violating data movement regulations. While data produced within these firewalled environments must be tightly controlled, ensuring consistency in data format enables confident data export to external applications.

The benefits of addressing these challenges are significant, particularly in terms of standardizing scalability and observability. Simplified expansion into new markets becomes a reality, no longer requiring long-term, costly strategies. Supply chain flexibility and international customer onboarding become streamlined processes. Moreover, improved data observability enhances the value of the data itself. Companies can verify data integrity, enhance data security, and achieve greater consistency, leading to more integrated management and reporting, which ultimately translates into increased value for the organization.

In conclusion, data sovereignty is shaping the future of businesses. Striking the right balance between centralized control and local execution is essential for effective data management. By addressing challenges across jurisdictional boundaries and firewalled environments, companies can achieve standardization, scalability, and observability, empowering them to thrive in a data-driven world.

thumbnail
Dr. Stefan Sigg

Dr. Stefan Sigg is the Chief Product Officer at Software AG. He has been a member of the Management Board of Software AG since April 2017 (under contract until 2027) and is responsible for Software AG's entire product portfolio, including global support, cloud operations, and research. Dr. Sigg earned both his master's degree and Ph.D. in mathematics from the University of Bonn, Germany. He started his professional career in SAP's product development unit in 1995. After several management positions, he took over the product leadership for SAP Business Warehouse, SAP HANA, and SAP Analytics. Additionally, Sigg has given courses and lectures on analytics, big data technologies, and IoT at the Technical University of Darmstadt since 2014. He is also a member of the following committees: Supervisory Board of the German Research Institute for Artificial Intelligence (DFKI), Board of Trustees of the Fraunhofer Institute for Secure Information Technologies, and the Supervisory Board of Fischer Information Technology AG.

Recommended for you...

Beyond Procurement: Optimizing Productivity, Consumer Experience with a Holistic Tech Management Strategy
Rishi Kohli
Jan 3, 2026
Why the Next Evolution in the C-Suite Is a Chief Data, Analytics, and AI Officer
AI Rewrites the Rules of IT Talent
Designing Data Pipelines for Scale: Principles for Reliability, Performance, and Flexibility
Luis Millares
Dec 19, 2025

Featured Resources from Cloud Data Insights

The Difficult Reality of Implementing Zero Trust Networking
Misbah Rehman
Jan 6, 2026
Cloud Evolution 2026: Strategic Imperatives for Chief Data Officers
Why Network Services Need Automation
The Shared Responsibility Model and Its Impact on Your Security Posture
RT Insights Logo

Analysis and market insights on real-time analytics including Big Data, the IoT, and cognitive computing. Business use cases and technologies are discussed.

Property of TechnologyAdvice. © 2026 TechnologyAdvice. All Rights Reserved

Advertiser Disclosure: Some of the products that appear on this site are from companies from which TechnologyAdvice receives compensation. This compensation may impact how and where products appear on this site including, for example, the order in which they appear. TechnologyAdvice does not include all companies or all types of products available in the marketplace.