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Implementing Analytics Solutions Using Microsoft Fabric
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Lesson 1: Get Started With Microsoft Fabric
1.1.1 Introduction to End-to-End Analytics Using Microsoft Fabric
1.1.2 Explore End-to-End Analytics with Microsoft Fabric
1.1.3 Data Teams and Microsoft Fabric
1.1.4 Enable and Use Microsoft Fabric
1.1.5 Summary
1.2.1 Introduction to Get started With Lakehouses in Microsoft Fabric
1.2.2 Explore the Microsoft Fabric Lakehouse
1.2.3 Work With Microsoft Fabric Lakehouses
1.2.4 Explore and Transform Data in a Lakehouse
1.2.5 Summary
1.3.1 Introduction to Use Apache Spark in Microsoft Fabric
1.3.2 Prepare to use Apache Spark
1.3.3 Run Spark Code
1.3.4 Connect to Data Sources and Ingest Data
1.3.5 Work With Data in a Spark Dataframe
1.3.6 Work With Data Using Spark SQL
1.3.7 Visualize Data in a Spark Notebook
1.3.8 Summary
1.4.1 Introduction to Work with Delta Lake Tables in Microsoft Fabric
1.4.2 Understand Delta Lake
1.4.3 Create Delta Tables
1.4.4 Create Delta Tables
1.4.5 Work With Delta Tables in Spark
1.4.6 Use Delta Tables With Streaming Data
1.4.7 Summary
1.5.1 Introduction to Orchestrate Processes and Data Movement With Microsoft Fabric
1.5.2 Understand Pipelines
1.5.3 Use the Copy Data Activity
1.5.4 Use Pipeline Templates
1.5.5 Run and Monitor Pipelines
1.5.6 Summary
1.6.1 Introduction to Ingest Data with Dataflows Gen2 in Microsoft Fabric
1.6.2 Understand Dataflows Gen2 in Microsoft Fabric
1.6.3 Explore Dataflows Gen2 in Microsoft Fabric
1.6.4 Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
1.6.5 Summary
1.7.1 Introduction to Get Started With Data Warehouses in Microsoft Fabric
1.7.2 Understand Data Warehouse Fundamentals
1.7.3 Understand Data Warehouses in Fabric
1.7.4 Query and Transform Data
1.7.5 Prepare Data for Analysis and Reporting
1.7.6 Secure and Monitor your Data Warehouse
1.7.7 Summary
1.8.1 Introduction to Get Started with Real-Time Intelligence in Microsoft Fabric
1.8.2 What is Real-Time Data Analytics?
1.8.3 Real-Time Intelligence in Microsoft Fabric
1.8.4 Ingest and Transform Real-Time Data
1.8.5 Store and Query Real-Time Data
1.8.6 Visualize Real-Time Data
1.8.7 Automate Actions
1.8.8 Summary
1.9.1 Introduction to Get Started With Data Science in Microsoft Fabric
1.9.2 Understand The Data Science Process
1.9.3 Explore and Process Data With Microsoft Fabric
1.9.4 Train and Score Models with Microsoft Fabric
1.9.5 Summary
1.10.1 Introduction to Administer a Microsoft Fabric Environment
1.10.2 Understand the Fabric Architecture
1.10.3 Understand the Fabric Administrator Role
1.10.4 Manage Fabric Security
1.10.5 Govern Data in Fabric
1.10.6 Summary
Lesson 2: Implement a Data Warehouse With Microsoft Fabric
2.1.1 Introduction to Get Started With Data Warehouses in Microsoft Fabric
2.1.2 Understand Data Warehouse Fundamentals
2.1.3 Understand Data Warehouses in Fabric
2.1.4 Query and Transform Data
2.1.5 Prepare Data for Analysis and Reporting
2.1.6 Secure and Monitor Your Data Warehouse
2.1.7 Summary
2.2.1 Introduction to Load Data Into a Microsoft Fabric Data Warehouse
2.2.2 Explore Data Load Strategies
2.2.3 Use Data Pipelines to Load a Warehouse
2.2.4 Load Data Using T-SQL
2.2.5 Load and Transform Data With Dataflow Gen2
2.2.6 Summary
2.3.1 Introduction to Query a Data Warehouse in Microsoft Fabric
2.3.2 Query Data
2.3.3 Use the SQL Query Editor
2.3.4 Explore The Visual Query Editor
2.3.5 Use Client Tools to Query a Warehouse
2.3.6 Summary
2.4.1 Introduction to Monitor a Microsoft Fabric Data Warehouse
2.4.2 Monitor Capacity Metrics
2.4.3 Monitor Current Activity
2.4.4 Monitor Queries
2.4.5 Summary
2.5.1 Introduction to Secure a Microsoft Fabric Data Warehouse
2.5.2 Explore Dynamic Data Masking
2.5.3 Implement Row-Level Security
2.5.4 Implement Column-Level Security
2.5.5 Configure SQL Granular Permissions Using T-SQL
2.5.6 Summary
Lesson 3: Work With Semantic Models in Microsoft Fabric
3.1.1 Introduction to Add Measures to Power BI Desktop Models
3.1.2 Create Simple Measures
3.1.3 Create Compound Measures
3.1.4 Create Quick Measures
3.1.5 Compare Calculated Columns With Measures
3.1.6 Summary
3.2.1 Introduction to Design Scalable Semantic Models
3.2.2 Choose The Best Storage Mode
3.2.3 Configure Semantic Models For Large Data
3.2.4 Work With Relationships
3.2.5 Write DAX for Readability With Complex Calculations
3.2.6 Create Dynamic Calculation Elements
3.2.7 Summary
3.3.1 Introduction to Performance Optimization
3.3.2 Review Performance of Measures, Relationships and Visuals Part - 1
3.3.3 Review Performance of Measures, Relationships and Visuals Part - 2
3.3.4 Use Variables to Improve Performance and Troubleshooting
3.3.5 Reduce Cardinality
3.3.6 Optimize DirectQuery Models With Table Level Storage
3.3.7 Create and Manage Aggregations
3.3.8 Summary
3.4.1 Introduction to Use Tools to Optimize Power BI Performance
3.4.2 Use Performance Analyzer
3.4.3 Troubleshoot DAX Performance by Using DAX Studio
3.4.4 Optimize a Data Model by Using Best Practice Analyzer
3.4.5 Summary
3.5.1 Introduction to Create and Manage Power BI Assets
3.5.2 Create Reusable Power BI Assets
3.5.3 Manage Development Lifecycle for Power BI Assets
3.5.4 Use Lineage View and Endorse Data Assets
3.5.5 Manage a Power BI Semantic Model Using XMLA Endpoint
3.5.6 Summary
3.6.1 Introduction to Enforce Power BI Model Security
3.6.2 Restrict Access to Power BI Model Data
3.6.3 Restrict Access to Power BI Model Objects
3.6.4 Apply Good Modeling Practices
3.6.5 Summary
Lesson 4: Administer and Govern Microsoft Fabric
4.1.1 Introduction to Administer a Microsoft Fabric Environment
4.1.2 Understand The Fabric Architecture
4.1.3 Understand The Fabric Administrator Role
4.1.4 Manage Fabric Security
4.1.5 Govern Data in Fabric
4.1.6 Summary
4.2.1 Introduction to Secure Data Access in Microsoft Fabric
4.2.2 Understand The Fabric Security Model
4.2.3 Configure Workspace and Item Permissions
4.2.4 Apply Granular Permissions
4.2.5 Summary
4.3.1 Introduction to Secure a Microsoft Fabric Data Warehouse
4.3.2 Explore Dynamic Data Masking
4.3.3 Implement Row-Level Security
4.3.4 Implement Column-Level Security
4.3.5 Configure SQL Granular Permissions Using T-SQL
4.3.6 Summary
4.4.1 Introduction to Govern Data in Microsoft Fabric With Purview
4.4.2 Govern Data in Microsoft Fabric
4.4.3 Why Use Microsoft Purview with Microsoft Fabric?
4.4.4 Govern Data in The Microsoft Purview Hub
4.4.5 Summary
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Implementing Analytics Solutions Using Microsoft Fabric
