Advancing Spark - Introduction to Featurestores
The last year saw an explosion of managed featurestores into the data science tooling market, but there's still a lot of confusion out there around what a featurestore actually is, and what problems they're solving. We'll be digging into the Databricks Featurestore in later videos, but first let's understand what they actually are! In this video, Simon welcomes back Gavi to give us a Featurestore history lesson and outline why we need them! As always, don't forget to like and subscribe - and if you're scaling out your data science capability and need help nailing the processes, get in touch with Advancing Analytics!

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Advancing Spark - Databricks Feature Store

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Advancing Spark - Getting Started with Ganglia in Databricks

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ML System Design: Feature Store

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Build & Deploy ML Churn model with FastAPI, MLFlow, Docker, & AWS

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Advancing Spark - Delta Sharing

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What is Spark? (Visual Explanation)

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Enable Production ML with Databricks Feature Store

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Apache Spark Architecture - EXPLAINED!

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Enhancing your Skills with Databricks Genie Code

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Advancing Spark - Getting Started with MLFlow Pipelines

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Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

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LakeBase from Databricks Is Changing Everything and People Are Mad!

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Accelerating Data Ingestion with Databricks Autoloader

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Rethinking Feature Stores

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Advancing Spark - Delta Deletion Vectors

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Inside Anthropic, the $965 Billion AI Juggernaut | The Circuit

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Advancing Spark - How to pass the Spark 3.0 accreditation!

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Advancing Spark - Give your Delta Lake a boost with Z-Ordering

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