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Data Warehouses Vs Operational Data Stores Vs Data Lakes – How To Store Your Data For Analytics

Seattle Data Guy

A few months ago, I uploaded a video where I discussed data warehouses, data lakes, and transactional databases. However, the world of data management is evolving rapidly, especially with the resurgence of AI and machine learning.

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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. Contact Info LinkedIn Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?

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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. Customers that require a hybrid of these to support many different tools and languages have built a data lakehouse.

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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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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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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. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. What kinds of data sources are you working with?

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Data Mesh vs Data Warehouse: 3 Key Differences 

Monte Carlo

Data mesh vs data warehouse is an interesting framing because it is not necessarily a binary choice depending on what exactly you mean by data warehouse (more on that later). Despite their differences, however, both approaches require high-quality, reliable data in order to function. What is a Data Mesh?