Microsoft Fabric – The Practical Guide

سرفصل های دوره

Master Microsoft Fabric from Foundation to Mastery: A Practical and Comprehensive Guide

1. Getting started with Fabric

1. What is Microsoft Fabric

2. Fabric Signup

3. Fabric without work email

4. Creating Fabric Workspace

5. Fabric Pricing

2. OneLake & Lakehouses

01. OneLake

02. Workspaces

03. Lakehouses

04. Exploring Workspaces

05. Create a lakehouse

06. Load data into lakehouse

07. Load data into tables

08. Exploring Delta Tables

09. Using Dataflow Gen 2

10. Using SQL analytics endpoint

3. Power BI & Semantic Models

1. Understanding semantic models

2. Using Semantic Models in Power BI

3. Create new semantic model

4. Creating measures

5. Connect to Fabric from Power BI Desktop

6. Using SQL endpoint

7. Auto Create Reports

8. Creating Apps

9. Updating & Deleting Apps

4. Data Factory

1. Azure Data Factory & Data Pipelines

2. Copy Data Activity

3. Adding DataFlow Gen 2 to Pipeline (Correct Version)

4. Disable Staging for better performance

5. Schedule Data Pipeline

6. Troubleshoot & Monitor Data Pipeline

5. Data Warehouses

01. What is a warehouse

02. Creating a data warehouse

03. Create Table Correct

04. INSERT & UPDATE data

05. Alter Table Schema

06. Calculating colmuns & Schema Updates

07. COPY INTO command

08. Copy Data using Pipeline

09. Referencing SQL endpoints from Lakehouses

10. Cloning tables

11. Modify Semantic Model and Create Reports

6. Data Engineering

01. Spark in Fabric

02. Creating a data frame

03. Exploring the notebooks

04. Uploading & reading files

05. Connect a lakehouse

06. Defining the schema

07. Filtering Data

08. Modify Schema

09. Adding columns

10. Aggregating & Grouping

11. Using functions

7. Real-Time Analytics

01. Basics of Real-Time Analytics in Fabric

02. Creating a KQL database

03. Basics of KQL

04. Sorting & Filtering

05. Aggregating & Grouping

06. Visulizing Data

07. Getting data

08. Joining data

09. Creating Eventstream

10. Event Processing

11. Routing streaming data to into KQL database

12. Connecting KQL database to Power BI

13. Ingesting stream into lakehouse

14. Real-time data in notebooks

15. Retention policies

16. Deleting Eventstream

8. Data Science

01. Data Science Introduction

02. Setup of Notebook & Load Data

03. Creating Pandas Dataframe

04. Data Cleansing using Data Wrangler

05. Exploratory Analysis - Distributions

06. Feature Impact Analysis

07. Feature Engineering

08. Connecting the results to Power BI

09. Setting up experiments & understanding models

10. Split and Sample Training Data

11. Train Model

12. Exploring Experiment & Metrics

13. Understanding ROC & Precision Recall Curve

14. Comparing different models

15. Save run as ML model

16. Applying the ML model

9. Data Activator

1. Data Activator Overview

2. Create Reflex from Power BI data

3. Setting up Triggers

4. Add data from Eventstream

5. Create Triggers from Objects

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تولید کننده: Udemy