pull base content,head:MicrosoftDocs:main,into:wwlpublishsync

Author: wwlpublish

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/1-introduction.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.introduction
-title: Introduction
-metadata:
-  title: Introduction
-  description: "Introduction"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 1
-content: |
-  [!include[](includes/1-introduction.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.introduction
+title: Introduction
+metadata:
+  title: Introduction
+  description: "Introduction"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 1
+content: |
+  [!include[](includes/1-introduction.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/2-explore-delta-live-tables.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.explore-delta-live-tables
-title: Explore Delta Live Tables
-metadata:
-  title: Explore Delta Live Tables
-  description: "Explore Delta Live Tables"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 5
-content: |
-  [!include[](includes/2-explore-delta-live-tables.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.explore-delta-live-tables
+title: Explore Delta Live Tables
+metadata:
+  title: Explore Delta Live Tables
+  description: "Explore Delta Live Tables"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 5
+content: |
+  [!include[](includes/2-explore-delta-live-tables.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/3-data-ingestion-and-integration.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.data-ingestion-and-integration
-title: Data ingestion and integration
-metadata:
-  title: Data ingestion and integration
-  description: "Data ingestion and integration"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 7
-content: |
-  [!include[](includes/3-data-ingestion-and-integration.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.data-ingestion-and-integration
+title: Data ingestion and integration
+metadata:
+  title: Data ingestion and integration
+  description: "Data ingestion and integration"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 7
+content: |
+  [!include[](includes/3-data-ingestion-and-integration.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/4-real-time-processing.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipelines-with-delta-live-tables.real-time-processing
-title: Real-time processing
-metadata:
-  title: Real-time processing
-  description: "Real-time processing"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 5
-content: |
-  [!include[](includes/4-real-time-processing.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipelines-with-delta-live-tables.real-time-processing
+title: Real-time processing
+metadata:
+  title: Real-time processing
+  description: "Real-time processing"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 5
+content: |
+  [!include[](includes/4-real-time-processing.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/5-exercise-data-pipeline.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.exercise-data-pipeline
-title: Exercise - Create a data pipeline with Delta Live Tables
-metadata:
-  title: Exercise - Create a data pipeline with Delta Live Tables
-  description: "Exercise - Create a data pipeline with Delta Live Tables"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 60
-content: |
-  [!include[](includes/5-exercise-data-pipeline.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.exercise-data-pipeline
+title: Exercise - Create a data pipeline with Delta Live Tables
+metadata:
+  title: Exercise - Create a data pipeline with Delta Live Tables
+  description: "Exercise - Create a data pipeline with Delta Live Tables"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 60
+content: |
+  [!include[](includes/5-exercise-data-pipeline.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/6-knowledge-check.yml

@@ -1,48 +1,48 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.knowledge-check
-title: Module assessment
-metadata:
-  title: Module assessment
-  description: "Knowledge check"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-azureSandbox: false
-labModal: false
-durationInMinutes: 3
-quiz:
-  questions:
-  - content: "What is the primary benefit of using Delta Live Tables (DLT) in Azure Databricks for real-time data processing?"
-    choices:
-    - content: "Reducing the cost of storage"
-      isCorrect: false
-      explanation: "Incorrect. Reducing the cost of storage isn't the primary benefit of using DLT in Azure Databricks for real-time processing."
-    - content: "Automating data pipeline management"
-      isCorrect: true
-      explanation: "Correct. Delta Live Tables is a framework that simplifies the management of data pipelines by automating complex tasks such as error handling, monitoring, and data pipeline lineage. This automation is valuable in real-time data processing, where managing data flows efficiently and reliably is critical."
-    - content: "Increasing the latency of data processing."
-      isCorrect: false
-      explanation: "Incorrect. Increasing the latency of data processing isn't the primary benefit of using DLT in Azure Databricks for real-time processing."
-  - content: "Which feature of Delta Live Tables ensures data reliability and quality in real-time processing environments?"
-    choices:
-    - content: "Live data"
-      isCorrect: false
-      explanation: "Incorrect. You can receive live data with real-time data processing with Delta Live tables but this feature doesn't ensure data reliability and quality."
-    - content: "ACID Transactions"
-      isCorrect: true
-      explanation: "Correct. Delta Live Tables support ACID transactions, which are crucial for ensuring data integrity by making all operations atomic, consistent, isolated, and durable. This is important in real-time processing environments where concurrent data modifications can lead to inconsistencies without proper transaction controls."
-    - content: "Data Lake"
-      isCorrect: false
-      explanation: "Incorrect. A Data Lake is a centralized repository that houses vast volumes of structured and unstructured data from various sources but it doesn't ensure data reliability and quality."
-  - content: "Which component of Azure Databricks enhances performance and scalability of data operations on Delta Lake?"
-    choices:
-    - content: "Azure Blob Storage"
-      isCorrect: false
-      explanation: "Incorrect. Azure Blob Storage is Microsoft's object storage solution for the cloud and isn't used to enhance performance and scalability of data operations on Delta Lake."
-    - content: "Azure Synapse Analytics"
-      isCorrect: false
-      explanation: "Incorrect. Azure Synapse Analytics is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems. It isn't used to enhance performance and scalability of data operations on Delta Lake."
-    - content: "Delta Engine"
-      isCorrect: true
-      explanation: "Correct. Delta Engine significantly enhances the performance and scalability of operations on Delta Lake in Azure Databricks. It optimizes the execution of queries by utilizing a high-performance, in-memory execution environment, which is crucial for processing large datasets efficiently."
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.knowledge-check
+title: Module assessment
+metadata:
+  title: Module assessment
+  description: "Knowledge check"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+azureSandbox: false
+labModal: false
+durationInMinutes: 3
+quiz:
+  questions:
+  - content: "What is the primary benefit of using Delta Live Tables (DLT) in Azure Databricks for real-time data processing?"
+    choices:
+    - content: "Reducing the cost of storage"
+      isCorrect: false
+      explanation: "Incorrect. Reducing the cost of storage isn't the primary benefit of using DLT in Azure Databricks for real-time processing."
+    - content: "Automating data pipeline management"
+      isCorrect: true
+      explanation: "Correct. Delta Live Tables is a framework that simplifies the management of data pipelines by automating complex tasks such as error handling, monitoring, and data pipeline lineage. This automation is valuable in real-time data processing, where managing data flows efficiently and reliably is critical."
+    - content: "Increasing the latency of data processing."
+      isCorrect: false
+      explanation: "Incorrect. Increasing the latency of data processing isn't the primary benefit of using DLT in Azure Databricks for real-time processing."
+  - content: "Which feature of Delta Live Tables ensures data reliability and quality in real-time processing environments?"
+    choices:
+    - content: "Live data"
+      isCorrect: false
+      explanation: "Incorrect. You can receive live data with real-time data processing with Delta Live tables but this feature doesn't ensure data reliability and quality."
+    - content: "ACID Transactions"
+      isCorrect: true
+      explanation: "Correct. Delta Live Tables support ACID transactions, which are crucial for ensuring data integrity by making all operations atomic, consistent, isolated, and durable. This is important in real-time processing environments where concurrent data modifications can lead to inconsistencies without proper transaction controls."
+    - content: "Data Lake"
+      isCorrect: false
+      explanation: "Incorrect. A Data Lake is a centralized repository that houses vast volumes of structured and unstructured data from various sources but it doesn't ensure data reliability and quality."
+  - content: "Which component of Azure Databricks enhances performance and scalability of data operations on Delta Lake?"
+    choices:
+    - content: "Azure Blob Storage"
+      isCorrect: false
+      explanation: "Incorrect. Azure Blob Storage is Microsoft's object storage solution for the cloud and isn't used to enhance performance and scalability of data operations on Delta Lake."
+    - content: "Azure Synapse Analytics"
+      isCorrect: false
+      explanation: "Incorrect. Azure Synapse Analytics is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems. It isn't used to enhance performance and scalability of data operations on Delta Lake."
+    - content: "Delta Engine"
+      isCorrect: true
+      explanation: "Correct. Delta Engine significantly enhances the performance and scalability of operations on Delta Lake in Azure Databricks. It optimizes the execution of queries by utilizing a high-performance, in-memory execution environment, which is crucial for processing large datasets efficiently."

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/7-summary.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables.summary
-title: Summary
-metadata:
-  title: Summary
-  description: "Summary"
-  ms.date: 07/23/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 3
-content: |
-  [!include[](includes/7-summary.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables.summary
+title: Summary
+metadata:
+  title: Summary
+  description: "Summary"
+  ms.date: 07/23/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 3
+content: |
+  [!include[](includes/7-summary.md)]

learn-pr/wwl-data-ai/build-data-pipeline-with-delta-live-tables/index.yml

@@ -1,38 +1,38 @@
-### YamlMime:Module
-uid: learn.wwl.build-data-pipeline-with-delta-live-tables
-metadata:
-  title: "Build data pipelines with Delta Live Tables"
-  description: "Learn how to build data pipelines with Delta Live Tables in Azure Databricks"
-  ms.date: "07/23/2024"
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: module-standard-task-based
-  ms.service: azure-databricks
-title: Build data pipelines with Delta Live Tables
-summary: "Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks"
-abstract: |
-  In this module, you'll learn how to:
-  - Describe Delta Live Tables
-  - Ingest data into Delta Live Tables
-  - Use Data Pipelines for real time data processing
-prerequisites: |
-  Before starting this module, you should be familiar the concept of a data pipeline.
-iconUrl: /training/achievements/generic-badge.svg
-levels:
-- intermediate
-roles:
-- data-analyst
-products:
-- azure-databricks
-subjects:
-- data-management
-units:
-- learn.wwl.build-data-pipeline-with-delta-live-tables.introduction
-- learn.wwl.build-data-pipeline-with-delta-live-tables.explore-delta-live-tables
-- learn.wwl.build-data-pipeline-with-delta-live-tables.data-ingestion-and-integration
-- learn.wwl.build-data-pipelines-with-delta-live-tables.real-time-processing
-- learn.wwl.build-data-pipeline-with-delta-live-tables.exercise-data-pipeline
-- learn.wwl.build-data-pipeline-with-delta-live-tables.knowledge-check
-- learn.wwl.build-data-pipeline-with-delta-live-tables.summary
-badge:
-  uid: learn.wwl.build-data-pipeline-with-delta-live-tables.badge
+### YamlMime:Module
+uid: learn.wwl.build-data-pipeline-with-delta-live-tables
+metadata:
+  title: "Build data pipelines with Delta Live Tables"
+  description: "Learn how to build data pipelines with Delta Live Tables in Azure Databricks"
+  ms.date: "07/23/2024"
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: module-standard-task-based
+  ms.service: azure-databricks
+title: Build data pipelines with Delta Live Tables
+summary: "Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks"
+abstract: |
+  In this module, you'll learn how to:
+  - Describe Delta Live Tables
+  - Ingest data into Delta Live Tables
+  - Use Data Pipelines for real time data processing
+prerequisites: |
+  Before starting this module, you should be familiar the concept of a data pipeline.
+iconUrl: /training/achievements/generic-badge.svg
+levels:
+- intermediate
+roles:
+- data-analyst
+products:
+- azure-databricks
+subjects:
+- data-management
+units:
+- learn.wwl.build-data-pipeline-with-delta-live-tables.introduction
+- learn.wwl.build-data-pipeline-with-delta-live-tables.explore-delta-live-tables
+- learn.wwl.build-data-pipeline-with-delta-live-tables.data-ingestion-and-integration
+- learn.wwl.build-data-pipelines-with-delta-live-tables.real-time-processing
+- learn.wwl.build-data-pipeline-with-delta-live-tables.exercise-data-pipeline
+- learn.wwl.build-data-pipeline-with-delta-live-tables.knowledge-check
+- learn.wwl.build-data-pipeline-with-delta-live-tables.summary
+badge:
+  uid: learn.wwl.build-data-pipeline-with-delta-live-tables.badge

learn-pr/wwl-data-ai/deploy-workloads-with-databricks-workflows/1-introduction.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.deploy-workloads-with-databricks-workflows.introduction
-title: Introduction
-metadata:
-  title: Introduction
-  description: "Introduction"
-  ms.date: 07/29/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 1
-content: |
-  [!include[](includes/1-introduction.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.deploy-workloads-with-databricks-workflows.introduction
+title: Introduction
+metadata:
+  title: Introduction
+  description: "Introduction"
+  ms.date: 07/29/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 1
+content: |
+  [!include[](includes/1-introduction.md)]

learn-pr/wwl-data-ai/deploy-workloads-with-databricks-workflows/2-what-are-azure-databricks-workflows.yml

@@ -1,13 +1,13 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.deploy-workloads-with-databricks-workflows.what-are-azure-databricks-workflows
-title: What are Azure Databricks Workflows?
-metadata:
-  title: What are Azure Databricks Workflows?
-  description: "What are Azure Databricks Workflows?"
-  ms.date: 07/29/2024
-  author: wwlpublish
-  ms.author: theresai
-  ms.topic: unit
-durationInMinutes: 5
-content: |
-  [!include[](includes/2-what-are-azure-databricks-workflows.md)]
+### YamlMime:ModuleUnit
+uid: learn.wwl.deploy-workloads-with-databricks-workflows.what-are-azure-databricks-workflows
+title: What are Azure Databricks Workflows?
+metadata:
+  title: What are Azure Databricks Workflows?
+  description: "What are Azure Databricks Workflows?"
+  ms.date: 07/29/2024
+  author: wwlpublish
+  ms.author: jamesh
+  ms.topic: unit
+durationInMinutes: 5
+content: |
+  [!include[](includes/2-what-are-azure-databricks-workflows.md)]