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.
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System Integration
Practical guides to data, integrations, enterprise platforms and applied AI.
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40 publications
Data governance and data lineage: quality for AI
The success of AI initiatives depends on data lineage transparency and Data Governance maturity. Learn how to avoid poor data quality traps and prepare enterprise IT architecture for AI scaling.
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.
AI agents in workflow: first-line processing and BPM future
How to combine the flexibility of AI with the rigid logic of BPMN 2.0 and DMN to automate first-line request processing without security risks or operational chaos.
Automation antipatterns: chaos, RPA, and AI risks
How to avoid cementing inefficiencies, replace fragile RPA scenarios with reliable API integrations, and safely implement AI into operational workflows using BPMN and DMN standards.
Managing automation projects: Process discovery, pilots, and continuous improvement
Why traditional process maps doom IT projects to failure and how to build effective automation based on real logs, BPMN 2.0, and DMN decision tables.
Overview of BPM platforms: process orchestration using BPMN 2.0 and DMN standards
An analysis of architectural approaches to business process automation. Comparing Scriptum, Camunda, Bonita, and UiPath to eliminate shadow processes and enable flexible modeling.
Low-code, RPA, or AI agent: choosing the right approach
Balancing deterministic orchestration and probabilistic AI in enterprise systems to avoid technical debt and critical security risks.
Process modeling standards: BPMN, CMMN, and DMN
Effective enterprise process automation requires separating workflow orchestration, flexible case management, and business rules. Learn how to avoid hardcoded logic and identify shadow routes.
Understanding BPM versus RPA and workflow automation
A guide to BPM, RPA, and workflow automation for IT architects. Learn how to combine BPMN, DMN, and Process Mining to avoid technical debt and achieve end-to-end orchestration.