Data Mesh and data products: future of system integration by 2027
Transitioning to a Data Mesh architecture resolves integration chaos through data decentralization, data contracts, and moving away from fragile point-to-point connections.
EXPERT / Digital Line
Kyrylo Fedorenko
Editorial contributor
About
Contributes Digital Line editorial materials on data, integration, enterprise platforms and practical AI use.
Articles with comments11Explore articles
Expert commentary
Current articles · 11Integrating legacy systems without APIs: CDC, facade services, and RPA limits
A practical analysis of architectural patterns for connecting legacy systems to modern ecosystems: how to avoid point-to-point chaos and why RPA is only a temporary solution.
Common integration mistakes that destroy IT architecture
Why ignoring organizational principles, lacking data owners, and "big bang" migrations doom corporate integration, and how to build a managed architecture.
Event-driven architecture: Kafka vs RabbitMQ and reliable event delivery
Comparing Kafka and RabbitMQ for building reliable event-driven architectures. Learn how to avoid integration issues and ensure data integrity.
When to use ESB versus point-to-point integration
Comparing architectural approaches: when direct connections become inefficient and how implementing an integration bus helps avoid complexity during scaling.
System integration and MDM: architectural patterns for scaling without chaos
Transitioning from point-to-point integrations to standardized EIP patterns, API Gateways, and managed Master Data Management to preserve corporate data integrity.
Integration architecture patterns for AI readiness: from chaos to Data Fabric
AI readiness is defined by architectural data maturity. Transitioning from point-to-point integrations to a managed layer with a unified API contract prevents data processing errors.
Who owns the customer master record: Data Governance for Customer 360
Effective customer data management requires clearly defined responsibilities for master record modifications, especially in the context of AI and cybersecurity.
Event-driven integration: Kafka or message queues for your business
Choosing between Apache Kafka and message queues for event-driven integration depends on scale, reliability, and cybersecurity requirements.
API Gateway with AI policies for microservice security
Integrating AI policies into API Gateways is critical for proactive microservice protection in 2027, countering cyber threats and AI-related risks.
AI у master: data management and system integration
AI analytics is transforming master data management (MDM) in 2026, ensuring accuracy and efficiency in enterprise system integration.