DP-600 Implementing Analytics Solutions Using Microsoft Fabric

سرفصل های دوره

1. Understand Microsoft Fabric Administration

1. Introducing Microsoft Fabric

2. Understand OneLake Architecture

3. License and Explore Fabric - And Power BI

4. Explore the Admin Settings

5. Other Administrative Dev Tools

6. CHALLENGE

2. Perform ETL Ops with Dataflows Gen2

1. Introducing Dataflows

2. Extract Data

3. Aggregate Data

4. Merge Data

5. Filter Data

6. Rank Data

7. Publish Data to a Lakehouse

8. Schedule Automatic Data Refreshes

9. CHALLENGE

3. Perform Complex ETL with Data Pipelines

1. Introducing Data Factory Pipelines

2. Create a Data Source in Azure

3. Create Your Dataflow to Transform Data

4. Prep the Data Destinations

5. Set the Data Destination and Create a Pipeline

6. Validate and Run the Pipeline

7. CHALLENGE

4. Implement and Explore Lakehouses

1. Introducing Fabric Lakehouses

2. Recall Why OneLake and Lakehouses Matter

3. Get Some Sample Data

4. Create a Lakehouse and Upload Data Files

5. Load Data Into Delta Tables

6. Explore the SQL Analytics Endpoint

7. Create a Shortcut

8. CHALLENGE

5. Build Queries and Reports on Lakehouse

1. Introducing Lakehouse Frontend Data Analysis

2. Understand Where Frontend Analytics Comes In

3. Create a Visual Query

4. Filter and Organize Data

5. Transform and Add Columns

6. Work with Semantic Models

7. Create Reports

8. CHALLENGE

6. Work with Data Warehouses

1. Introducing Data Warehouses

2. Creating a Data Warehouse

3. Perform DDL Operations

4. INSERT and UPDATE Operations

5. Alter Tables... Sort of

6. Update Records with Calculations

7. Copy Data From External Sources with COPY INTO

8. CHALLENGE

7. Work with Spark Notebooks

1. Introducing Fabric Notebooks

2. What Spark Really Is

3. Load Data Into Spark Notebooks

4. Set and Alter Schema Data Types and Columns

5. Filter Data

6. Aggregate, Group, and Sort Data

7. CHALLENGE

8. Integrate Spark Notebooks with Lakehouse

1. Introducing Data Querying and Writing in Notebooks

2. Join Dataframes

3. Write Files to a Lakehouse

4. Write Data to Delta Tables

5. Querying with SQL and Python

6. Scheduling and Orchestrating Notebooks

7. CHALLENGE

9. Begin Work with Semantic Models

1. Introducing Semantic Models

2. Get Some Data

3. Create Semantic Model Relationships

4. Auto-Generate a Report from Your Model

5. Create DAX Measures

6. Connect to Fabric with Power BI Desktop

7. Connect to the SQL Analytics Endpoint

8. Publish Apps

9. CHALLENGE

10. Design Semantic Models

1. Introducing Semantic Model Design

2. Dimensions and Facts

3. Star and Snowflake Schema

4. 1st Form Normalization

5. 2nd and 3rd Form Normalization

6. What Works Best for Analytics

7. Merge Queries in Power Query

8. CHALLENGE

11. Learn DAX Fundamentals

1. Introducing DAX and DAX Studio

2. Install DAX Studio

3. EVALUATE

4. ORDER BY and FILTER

5. SUMMARIZECOLUMNS

6. Basic DAX Aggregations

7. DEFINE

8. Iterator - or X Functions

9. CALCULATE

10. Datetime Functions

11. CHALLENGE

12. Use External Semantic Modeling Apps

1. Introducing External Modeling Tools

2. DAX Studio Performance Analysis

3. DAX Studio VertiPaq Analyzer

4. ALM Toolkit

5. Install and Browse Tabular Editor

6. Use Tabular Editor Best Practices Analyzer

7. Object Level Security

8. Row Level Security

9. CHALLENGE

13. Implement Calculation Groups

1. Introduction

2. Understand Measure Sprawl

3. Create a Calculation Group

4. Create Calculation Items

5. Use Calculation Groups in a Report

6. Add Field Parameters to Switch Measures

7. Create Calculation Groups in Power BI

8. CHALLENGE

14. Leverage the XMLA Endpoint

1. Introducing the XMLA Endpoint

2. Understand the Point of XMLA

3. Governance and Configuration

4. Connect and Query with SSMS

5. Download and Deploy Models with Tabular Editor

6. Query Models with DAX Studio

7. Compare and Ship Models with ALM Toolkit

8. CHALLENGE

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