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Introduction to Databricks Lakehouse
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更新済み 2026/05
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DatabricksData Engineering3 時間15 ビデオ43 演習3,550 XP修了証明書
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Understand the Lakehouse Architecture
Start by discovering what sets the lakehouse apart from traditional approaches. You'll explore the medallion architecture — bronze, silver, and gold layers — that transforms raw, messy data into clean, business-ready insights. Then get oriented inside the Databricks workspace to understand how catalogs, schemas, and volumes organize everything.Master Compute and Notebooks
Learn to choose the right cluster for the job, configure autoscaling and auto-termination to control costs, and build notebooks that mix Python, SQL, and Markdown. You'll also connect your work to Git through Databricks Repos for version control and team collaboration.Govern and Share Data Securely
Explore Unity Catalog to manage access controls and track data lineage across your organization. Then use Delta Sharing to distribute data to partners — on Databricks or any other platform — and query external sources with Lakehouse Federation, all without copying a single byte.Deploy to Production with Asset Bundles
Wrap up by packaging your notebooks, pipelines, and jobs into Databricks Asset Bundles for repeatable, automated deployments. A capstone scenario brings everything together so you leave ready to apply these skills on the job.前提条件
Introduction to Databricks1
The Lakehouse Paradigm
Discover what makes the lakehouse different from traditional architectures, how the medallion pattern organizes data, and where things live inside the Databricks platform.
2
Compute and Notebooks
Spin up the right cluster for the job, configure it for cost and performance, master the notebook environment, and connect your work to Git - all inside the Databricks workspace.
3
Governance and Sharing
Lock down your data with Unity Catalog, share it securely with Delta Sharing, and federate queries to external sources - all without copying a single byte.
4
Deployment and Next Steps
Package your work with Databricks Asset Bundles, deploy to production, and bring everything together in a capstone scenario.
Introduction to Databricks Lakehouse
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