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A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1

Cloudera

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

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Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera

Data Engineering Podcast

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

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The Data Integration Solution Checklist: Top 10 Considerations

Precisely

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

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The View Below The Waterline Of Apache Iceberg And How It Fits In Your Data Lakehouse

Data Engineering Podcast

Summary Cloud data warehouses have unlocked a massive amount of innovation and investment in data applications, but they are still inherently limiting. Because of their complete ownership of your data they constrain the possibilities of what data you can store and how it can be used.

IT 147
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Is Modern Data Warehouse Architecture Broken? 

Monte Carlo

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. Treating data like an API. Immutable data warehouses have challenges too.

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Extreme data center pressure? Burst to the cloud with CDP!

Cloudera

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. A solution.

Cloud 102
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Toward a Data Mesh (part 2) : Architecture & Technologies

François Nguyen

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How can we interoperate between the data domains ? How do we govern all these data products and domains ? It will be illustrated with our technical choices and the services we are using in the Google Cloud Platform.