Topic

Cloud Computing

Data

Federated data quality governance: Balancing control and autonomy

Discover how to establish and maintain a federated data quality governance model that combines centralized standards with domain autonomy in distributed architectures. This approach is critical for preventing data fragmentation and ensuring data reliability.

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Data

Data 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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Support

Observability architecture: Complete transparency for IT systems

Implementing a comprehensive Observability architecture provides deep insights into the internal state of distributed IT systems, which is key to ensuring their stability and rapid problem localization. This strategic approach goes beyond traditional monitoring, delivering context-rich insights.

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Data

Balancing compliance and costs in multi-cloud data archiving

Managing data archiving and retention in multi-cloud and hybrid environments presents significant challenges for enterprises. This article explores how to develop and implement a consistent and compliant strategy that optimizes costs and ensures data availability.

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Integration

Multi-cloud data integration: A unified data fabric for the enterprise

Building a unified data fabric across hybrid and multi-cloud environments is critical for operational continuity and advanced analytics. This requires a balanced approach to data management, security, and performance.

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Data

Data 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.

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Data

Data residency and sovereignty: Cloud compliance for large enterprises

Increasing regulatory pressure and geopolitical factors make data residency and sovereignty critical for any enterprise handling sensitive information or operating in international markets. This article offers practical architectural solutions for CIOs/CTOs.

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Data

Choosing data architecture for real-time AI/ML

Selecting the optimal data architecture (batch, streaming, or hybrid) is critical for supporting real-time AI/ML model training and inference. This decision balances latency, cost, and system complexity.

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