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Building A Real Time Event Data Warehouse For Sentry

Data Engineering Podcast

Summary The team at Sentry has built a platform for anyone in the world to send software errors and events. As they scaled the volume of customers and data they began running into the limitations of their initial architecture. What are some of the downstream benefits of using Clickhouse for managing event data at Sentry?

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How Shopify Is Building Their Production Data Warehouse Using DBT

Data Engineering Podcast

In this episode Zeeshan Qureshi and Michelle Ark share their experiences using DBT to manage the data warehouse for Shopify. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm.

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Building A Better Data Warehouse For The Cloud At Firebolt

Data Engineering Podcast

Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage.

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SnowflakeDB: The Data Warehouse Built For The Cloud

Data Engineering Podcast

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. If you are evaluating your options for building or migrating a data platform, then this is definitely worth a listen.

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Keeping Your Data Warehouse In Order With DataForm

Data Engineering Podcast

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data management.

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Mastering the Art of ETL on AWS for Data Management

ProjectPro

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. ETL has typically been carried out utilizing data warehouses and on-premise ETL tools.

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Charting A Path For Streaming Data To Fill Your Data Lake With Hudi

Data Engineering Podcast

Vinoth Chandar helped to create the Hudi project while at Uber to address this challenge. By adding support for small, incremental inserts into large table structures, and building support for arbitrary update and delete operations the Hudi project brings the best of both worlds together. Can you describe how Hudi is architected?

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