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Modern Customer Data Platform Principles

Data Engineering Podcast

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. How has that changed the architectural approach to CDPs?

Data Lake 147
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Data Engineering Weekly #107

Data Engineering Weekly

It moved from the speculation to the data engineers understanding the benefit of it and asking when we can get the implementation soon. I met many data leaders about Data Contracts, my project Schemata, and how the extended version we are building can help them create high-quality data.

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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Another common breaking schema change scenario is when data teams sync their production database with their data warehouse as is the case with Freshly.

Data 52
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61 Data Observability Use Cases That Aren’t Totally Made Up

Monte Carlo

Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Another common breaking schema change scenario is when data teams sync their production database with their data warehouse as is the case with Freshly.