Remove Data Management Remove Data Warehouse Remove Technology
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Use Your Data Warehouse To Power Your Product Analytics With NetSpring

Data Engineering Podcast

In this episode Priyendra Deshwal explains how NetSpring is designed to empower your product and data teams to build and explore insights around your products in a streamlined and maintainable workflow. How is the NetSpring platform implemented to be able to best take advantage of modern warehouse technologies and the associated data stacks?

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Use cases change, needs change, technology changes – and therefore data infrastructure should be able to scale and evolve with change.

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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. In the world of technology, things are always changing. It is especially true in the world of big data.

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Building Your Data Warehouse On Top Of PostgreSQL

Data Engineering Podcast

Summary There is a lot of attention on the database market and cloud data warehouses. While they provide a measure of convenience, they also require you to sacrifice a certain amount of control over your data. Firebolt is the fastest cloud data warehouse. Visit dataengineeringpodcast.com/firebolt to get started.

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How Shopify Is Building Their Production Data Warehouse Using DBT

Data Engineering Podcast

Summary With all of the tools and services available for building a data platform it can be difficult to separate the signal from the noise. One of the best ways to get a true understanding of how a technology works in practice is to hear from people who are running it in production. What kinds of data sources are you working with?

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Creating Shared Context For Your Data Warehouse With A Controlled Vocabulary

Data Engineering Podcast

In this episode Emily Riederer shares her work to create a controlled vocabulary for managing the semantic elements of the data managed by her team and encoding it in the schema definitions in her data warehouse. star/snowflake schema, data vault, etc.) What do you have planned for the future of dbtplyr?

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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.