GDPR
DataData consistency in distributed systems: Choosing a model for business processes
Selecting a data consistency model in distributed systems – from strong to eventual – is a key architectural trade-off affecting operational reliability and the quality of business decisions. This decision requires understanding the impact on availability, performance, and latency for critical business processes.
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IntegrationTechnical compliance for data sharing agreements
Ensuring compliance when exchanging data with external partners demands translating legal obligations into concrete technical controls within integrated systems. This includes implementing granular access control, data masking, and secure API gateways.
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DataAccessing sensitive data for AI/ML: Balancing innovation and compliance
Ukrainian companies face a critical challenge: how to utilize sensitive data for AI/ML while adhering to data protection laws. This article provides practical strategies and architectural approaches to resolve the conflict between innovation and compliance.
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DataData Lakehouse or Data Mesh: Choosing the right architecture for compliance in Ukraine
Choosing the optimal data architecture (Data Lakehouse vs. Data Mesh) is crucial for Ukrainian businesses, considering national legislation and GDPR requirements for data protection and sovereignty. This decision impacts flexibility, scalability, and the ability to adhere to regulatory norms.
Read articleMDM without centralization: Defining master system boundaries
Defining the boundaries of master systems is a critical architectural decision for successful MDM. This approach helps avoid excessive centralization and ensures data quality.
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