added videos

weslbo · weslbo · commit acbe4f7c01fd · 2026-01-19T09:02:07.000+01:00
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/01-introduction.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/01-introduction.yml
@@ -4,7 +4,7 @@ title: Introduction
 metadata:
   title: Introduction
   description: "Introduction"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/02-azure-databricks.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/02-azure-databricks.yml
@@ -4,7 +4,7 @@ title: Get started with Azure Databricks
 metadata:
   title: Get Started With Azure Databricks
   description: "Get started with Azure Databricks"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/03-workloads.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/03-workloads.yml
@@ -4,7 +4,7 @@ title: Identify Azure Databricks workloads
 metadata:
   title: Identify Azure Databricks Workloads
   description: "Identify Azure Databricks workloads"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/04-key-concepts.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/04-key-concepts.yml
@@ -4,7 +4,7 @@ title: Understand key concepts
 metadata:
   title: Understand Key Concepts
   description: "Understand key concepts"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/05-data-governance-using-unity-catalog-and-microsoft-purview.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/05-data-governance-using-unity-catalog-and-microsoft-purview.yml
@@ -4,7 +4,7 @@ title: Data governance using Unity Catalog and Microsoft Purview
 metadata:
   title: Data Governance Using Unity Catalog and Microsoft Purview
   description: "Data governance using Unity Catalog and Microsoft Purview"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/06-exercise-explore-databricks.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/06-exercise-explore-databricks.yml
@@ -4,7 +4,7 @@ title: Exercise - Explore Azure Databricks
 metadata:
   title: Exercise - Explore Azure Databricks
   description: "Exercise - Explore Azure Databricks"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/07-knowledge-check.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/07-knowledge-check.yml
@@ -4,7 +4,7 @@ title: Module assessment
 metadata:
   title: Module Assessment
   description: "Knowledge check"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/08-summary.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/08-summary.yml
@@ -4,7 +4,7 @@ title: Summary
 metadata:
   title: Summary
   description: "Summary"
-  ms.date: 09/12/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: unit
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/includes/01-introduction.md b/learn-pr/wwl-data-ai/explore-azure-databricks/includes/01-introduction.md
@@ -1,4 +1,4 @@
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-01]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=c959967a-8be3-42d8-a78a-a2c54ee1d1c2]
 
 Azure Databricks is a cloud-based data platform that brings together the best of **data engineering, data science, and machine learning** in a single, unified workspace. Built on top of **Apache Spark**, it allows organizations to easily process, analyze, and visualize massive amounts of data in real time.
 
@@ -18,7 +18,7 @@ At its core, Azure Databricks helps organizations:
 
 ## Data Lakehouse
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-02]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=fe88876f-1235-4ce0-ac98-9f0376d61781]
 
 A **data lakehouse** is a data management approach that blends the strengths of both data lakes and data warehouses. It offers scalable storage and processing, allowing organizations to handle diverse workloads—such as machine learning and business intelligence—without relying on separate, disconnected systems. By centralizing data, a lakehouse supports a single source of truth, reduces duplicate costs, and ensures that information stays up to date.
 
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/includes/02-azure-databricks.md b/learn-pr/wwl-data-ai/explore-azure-databricks/includes/02-azure-databricks.md
@@ -1,4 +1,4 @@
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-03]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=d4fcf5c1-5d99-439c-8bba-157f93385e15]
 
 To use Azure Databricks, you must create an Azure Databricks workspace in your Azure subscription. A workspace is an Azure Databricks deployment in a cloud service account. It provides a unified environment for working with Azure Databricks assets for a specified set of users.
 
@@ -62,7 +62,7 @@ The workspace is available in **multiple languages.** To change the workspace la
 
 ## Get help from Databricks Assistant
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-04]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=06416086-5e53-47c0-8804-8387d1973871]
 
 **Databricks Assistant** is an AI-powered pair programmer and support tool that helps you work more efficiently in Databricks by generating, explaining, and fixing code or queries directly in notebooks, dashboards, and files. 
 
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/includes/03-workloads.md b/learn-pr/wwl-data-ai/explore-azure-databricks/includes/03-workloads.md
@@ -2,23 +2,23 @@ Azure Databricks offers capabilities for various workloads including Machine Lea
 
 ## Data Engineering
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-05]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=142999cd-f832-426e-b39c-02365db09957]
 
 Azure Databricks provides capabilities for data scientists and engineers who need to collaborate on complex data processing tasks. It provides an integrated environment with Apache Spark for big data processing in a data lakehouse, and supports multiple languages including Python, R, Scala, and SQL. The platform facilitates data exploration, visualization, and the development of data pipelines.
 
 :::image type="content" source="../media/03-azure-databricks-data-science-engineering.png" alt-text="Diagram of Databricks data ingestion & data sources screen." lightbox="../media/03-azure-databricks-data-science-engineering.png":::
 
 ## Machine Learning
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-06]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=507d0d61-269c-460f-b17f-c8ab190041f7]
 
 Azure Databricks supports building, training, and deploying machine learning models at scale. It includes MLflow, an open-source platform to manage the ML lifecycle, including experimentation, reproducibility, and deployment. It also supports various ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, making it versatile for different ML tasks.
 
 :::image type="content" source="../media/04-azure-databricks-machine-learning.png" alt-text="Diagram of Databricks Machine Learning screen." lightbox="../media/04-azure-databricks-machine-learning.png":::
 
 ## SQL
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-07]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=c86c4c0b-b84a-48e6-b3bc-8a33d30136bd]
 
 Data analysts who primarily interact with data through SQL can use SQL warehouses in Azure Databricks. The Azure Databricks Workspace UI provides a familiar SQL editor, dashboards, and automatic visualization tools to analyze and visualize data directly within Azure Databricks. This workload is ideal for running quick ad-hoc queries and creating reports from large datasets.
 
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/includes/04-key-concepts.md b/learn-pr/wwl-data-ai/explore-azure-databricks/includes/04-key-concepts.md
@@ -2,7 +2,7 @@ Azure Databricks is a single service platform with multiple technologies that en
 
 ## Workspaces
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-08]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=bd32efc6-01aa-4c6b-811c-14c5109d9a3c]
 
 A **workspace** in Azure Databricks is a secure, collaborative environment where your can access and organize all Databricks assets, such as notebooks, clusters, jobs, libraries, dashboards, and experiments. 
 
@@ -16,7 +16,7 @@ In addition, workspaces are tied to **Unity Catalog** (when enabled) for central
 
 ## Notebooks
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-888888888-09]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=043554e4-b9f6-4566-90ab-6071ffc27eba]
 
 **Databricks notebooks** are interactive, web-based documents that combine **runnable code, visualizations, and narrative text** in a single environment. They support multiple languages—such as Python, R, Scala, and SQL—and allow users to switch between languages within the same notebook using *magic commands*. This flexibility makes notebooks well-suited for **exploratory data analysis, data visualization, machine learning experiments, and building complex data pipelines**.
 
@@ -28,7 +28,7 @@ Notebooks contain a collection of two types of cells: **code cells** and **Markd
 
 ## Clusters
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-10]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=85a4a208-66db-4059-a4f0-9ba951818fc3]
 
 Azure Databricks leverages a two-layer architecture:
 
@@ -49,7 +49,7 @@ This allows you to tailor compute to specific needs—from exploratory analysis
 
 ## Databricks Runtime
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-11]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=0963a8a9-2beb-4b23-8edb-cc2401fbf74e]
 
 The **Databricks Runtime** is a set of customized builds of **Apache Spark** that include performance improvements and additional libraries. These runtimes make it easier to handle tasks such as **machine learning**, **graph processing**, and **genomics**, while still supporting general data processing and analytics.
 
@@ -64,7 +64,7 @@ If a maintenance update is released for a runtime version you're using, you can
 
 ## Lakeflow Jobs
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-12]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=b50ca343-fcd9-4070-b6a1-1e4fcde9d606]
 
 **Lakeflow Jobs** provide workflow automation and orchestration in Azure Databricks, making it possible to reliably schedule, coordinate, and run data processing tasks. Instead of running code manually, you can use jobs to automate repetitive or production-grade workloads such as ETL pipelines, machine learning training, or dashboard refreshes.
 
@@ -82,7 +82,7 @@ Because they're repeatable and managed, jobs are critical for **production workl
 
 ## Delta Lake
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-13]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=3eb8bdba-9207-4733-9ed7-d08369734f9e]
 
 **Delta Lake** is an open-source storage framework that improves the reliability and scalability of data lakes by adding transactional features on top of cloud object storage, such as **Azure Data Lake Storage**. Traditional data lakes can suffer from issues like inconsistent data, partial writes, or difficulties managing concurrent access. Delta Lake addresses these problems by supporting:
 
@@ -95,7 +95,7 @@ On top of this foundation, **Delta tables** provide a familiar table abstraction
 
 ## Databricks SQL
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-14]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=0aef1e6c-12e3-40f5-b04c-ecd1db01e153]
 
 **Databricks SQL** brings **data warehousing capabilities** to the Databricks Lakehouse, allowing analysts and business users to query and visualize data stored in open formats directly in the data lake. It supports **ANSI SQL**, so anyone familiar with SQL can run queries, build reports, and create dashboards without needing to learn new languages or tools.
 
@@ -107,7 +107,7 @@ Databricks SQL is available only in the **Premium tier** of Azure Databricks. It
 
 ## SQL Warehouses
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-15]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=fa507047-6226-4ba4-9a9a-c0d2a95ba01b]
 
 All Databricks SQL queries run on **SQL warehouses** (formerly called SQL endpoints), which are scalable compute resources decoupled from storage. Different warehouse types are available depending on performance, cost, and management needs:
 
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/includes/05-data-governance-using-unity-catalog-and-microsoft-purview.md b/learn-pr/wwl-data-ai/explore-azure-databricks/includes/05-data-governance-using-unity-catalog-and-microsoft-purview.md
@@ -1,4 +1,4 @@
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-16]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=ae2e4976-0a38-4e28-a6bc-0622b7d00079]
 
 Data governance is critical for ensuring that data within an organization is managed securely, efficiently, and in compliance with regulations. 
 
@@ -16,7 +16,7 @@ Azure Databricks, combined with Unity Catalog and Microsoft Purview, provides a
 
 ## Unity Catalog 
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-17]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=72b4857c-6be6-421e-a53f-c672e53c5d33]
 
 Unity Catalog provides a centralized way to manage access, discovery, lineage, audit logs, and quality monitoring across data and AI assets within Azure Databricks. It applies consistently across all workspaces in a region.
 
@@ -50,7 +50,7 @@ In most accounts, Unity Catalog is enabled by default when you create a workspac
 
 ## Microsoft Purview
 
->[!VIDEO https://learn-video.azurefd.net/vod/player?id=22222222-2222-2222-8888-8888888888-18]
+>[!VIDEO https://learn-video.azurefd.net/vod/player?id=0e72769b-ae7e-4b3a-881e-0e52b1523347]
 
 Microsoft Purview is a data governance service that lets you manage and oversee data across on-premises systems, multiple clouds, and SaaS platforms. It includes features such as data discovery, classification, lineage tracking, and access governance.
 
diff --git a/learn-pr/wwl-data-ai/explore-azure-databricks/index.yml b/learn-pr/wwl-data-ai/explore-azure-databricks/index.yml
@@ -3,7 +3,7 @@ uid: learn.wwl.explore-azure-databricks
 metadata:
   title: Explore Azure Databricks
   description: Explore Azure Databricks
-  ms.date: 12/09/2025
+  ms.date: 01/19/2026
   author: weslbo
   ms.author: wedebols
   ms.topic: module
