WeAreDevelopers LIVE • May 26, 2021

The Data Mesh as the end of the Datalake as we know it

Mario Meir-Huber

Centralized data lakes have failed modern enterprises. Discover how the data mesh embraces decentralized architecture to eliminate bottlenecks and empower domain experts.

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#1 about 8 min

Data challenges in large enterprise environments

Distributed ownership and legacy systems create data silos that hinder technical innovation in large corporations.

#2 about 2 min

The limitations of early centralized data warehouses

High storage costs and rigid formats limited the long-term success of early centralized data warehouses.

#3 about 4 min

The governance failures of centralized data lakes

Centralizing information into Hadoop-based data lakes often resulted in poor data governance and technical overhead.

#4 about 2 min

Understanding data mesh as an organizational design shift

Treating data management as an organizational shift rather than a technical deployment prevents repetitive decentralization issues.

#5 about 6 min

Shifting focus from monolithic pipelines to business domains

Shifting focus away from complex ETL pipelines and monoliths accelerates delivery for actual business problems.

#6 about 6 min

Applying distributed domain-driven architecture to enterprise data

Empowering business domains with decentralized data ownership mirrors agile microservices architectures and removes IT bottlenecks.

#7 about 4 min

Adopting self-serve managed platforms for data infrastructure

Using managed cloud platforms prevents infrastructure reinventing and allows teams to focus entirely on data workloads.

#8 about 9 min

Treating enterprise data sets as internal products

Defining data as a discoverable and trustworthy internal product ensures quality access for cross-functional teams.

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