What you'll learn

Students will learn how to build warehouse and lakehouses on Microsoft Fabric.
Students will learn on how to build semantic models in Power BI Desktop.
Students will learn SQL aspects and how to ingest data into Microsoft Fabric.
Students will also learn about several security aspects around Microsoft Fabric.

Requirements

No prior knowledge on Microsoft Fabric is required, students will learn about Microsoft Fabric.
No prior knowledge is required for Power BI Desktop, we will learn about Power BI Desktop in this course.

Description

"This course requires you to download Power BI Desktop on your local machine. If you are a Udemy Business user, please check with your employer before downloading software."This intensive, comprehensive course is designed to prepare data professionals for the Microsoft DP-600 certification exam, focusing on data warehouse implementation and optimization using Microsoft Fabric. Participants will gain the knowledge and practical skills necessary to design, implement, and manage semantic models, data warehouses , lakehouses that leverage the full power of Microsoft's modern data analytics platform.What are we going to learnBasics around data and getting the required tools in place for the course.Getting and transforming data within Power BI Desktop.Building various aspects in Power BI Desktop such reports, visualizations, Measures etc.How to use Power Query in Power BI Desktop to transform data. We will see an example on how build a semantic model around Fact and Dimension tables.Getting started with Microsoft Fabric. How we get trial capacity to start working with the service.How we can build data warehouses in Microsoft Fabric. Using T-SQL, data pipelines and Data Flow Gen2 we can see how to ingest data into Microsoft Fabric.How to run basic T-SQL commands against our data warehouse.How to build Lakehouses on Microsoft Fabric.How we can ingest data into Lakehouses using data pipelines and Data Flow Gen2.How to use Apache Spark in Microsoft Fabric to work with data sets.

Overview

Section 1: Introduction
Lecture 1 Data in today's world
Lecture 2 Tools and services
Lecture 3 Microsoft Power BI
Lecture 4 Lab - Installing Power BI Desktop
Lecture 5 Tour of Power BI Desktop
Lecture 6 Our data sets
Lecture 7 Setting up an Azure Free Tier Account
Lecture 8 About the Azure SQL database service
Lecture 9 Creating an Azure SQL database server
Lecture 10 Setting up the Azure SQL database
Section 2: Implement and manage semantic models - Power BI Desktop
Lecture 11 Section Resources
Lecture 12 Lab - Power BI Desktop - Get Data
Lecture 13 Lab - Power BI Desktop - Removing columns
Lecture 14 Lab - Power BI Desktop - Handing missing values
Lecture 15 Lab - Power BI Desktop - Adding new columns
Lecture 16 Online Analytical Processing Systems
Lecture 17 What goes into building a data warehouse
Lecture 18 Power BI Desktop - Merge Queries
Lecture 19 Lab - Power BI Desktop - Merge Queries - DimProduct
Lecture 20 Lab - Power BI Desktop - Merge Queries - DimCustomer
Lecture 21 Lab - Power BI Desktop - Merge Queries - FactSales
Lecture 22 Different views in Power BI Desktop
Lecture 23 What are we going to do next
Lecture 24 Lab - Power BI Desktop - Building simple visualizations
Lecture 25 Lab - Power BI Desktop - Hierarchies
Lecture 26 Power BI Desktop - Quick look at drill down
Lecture 27

Overview

on DAX
Lecture 28 Lab - DAX Expressions - Creating a measure
Lecture 29 Lab - DAX Expressions - Aggregation Functions
Lecture 30 Lab - DAX Expressions - Filter Functions
Lecture 31 Lab - DAX Expressions - Information Functions
Lecture 32 Lab - DAX Expressions - Using Quick measures
Lecture 33 Lab - Power BI Desktop - Building the Date Dimension table
Lecture 34 Lab - Power BI Desktop - Using calculation groups
Lecture 35 Lab - Power BI Desktop - Using Field parameters
Lecture 36 Semantic Model - Storage Design
Lecture 37 Lab - Using the Direct Query mode
Lecture 38 Power BI Desktop - ColumnProfiling tools
Lecture 39 Quick note on other performance considerations in Power BI Desktop
Lecture 40 Lab - Power BI Desktop - Performance Analyzer
Section 3: Prepare Data - Microsoft Fabric - Data Ingestion and Data warehouse
Lecture 41 Section Code
Lecture 42 What is Microsoft Fabric
Lecture 43 Microsoft Fabric terms
Lecture 44 Note on Microsoft Fabric Licensing
Lecture 45 On-boarding ourselves onto Microsoft Fabric
Lecture 46 Getting Microsoft Fabric Trial capacity
Lecture 47 Lab - Publishing a report from Power BI Desktop to Fabric
Lecture 48 Review of the data warehousing fundamentals
Lecture 49 Lab - Microsoft Fabric - Creating a sample data warehouse
Lecture 50 Microsoft Fabric - Ingesting data
Lecture 51 Lab - Creating an Azure Storage Account
Lecture 52 Lab - Microsoft Fabric data warehouse - Ingesting data - COPY command
Lecture 53 Lab - Microsoft Fabric data warehouse - Ingesting data - COPY command - SAS
Lecture 54 Lab - Microsoft Fabric data warehouse - Visual Query
Lecture 55 Lab - Microsoft Fabric data warehouse - Cloning tables
Lecture 56 Lab - Microsoft Fabric warehouse - CREATE TABLE AS SELECT
Lecture 57 Lab - Microsoft Fabric - Ingesting data - Data Pipeline
Lecture 58 Lab - Microsoft Fabric - Ingesting data - Data Flow Gen2
Lecture 59 Lab - Microsoft Fabric data warehouse - Building our Fact table
Lecture 60 Lab - Microsoft Fabric data warehouse - Building our Dimension tables
Lecture 61 Lab - Microsoft Fabric data warehouse - Building the Dimension Date table
Lecture 62 Lab - Microsoft Fabric data warehouse - Default semantic model
Lecture 63 Lab - Microsoft Fabric data warehouse - Column profiling
Lecture 64 Data warehouse - Slowly Changing Dimensions
Lecture 65 Microsoft Fabric - Power Query - Query folding
Lecture 66 Lab - Microsoft Fabric data warehouse - SQL - Basics
Lecture 67 Lab - Microsoft Fabric data warehouse - SQL - Group by
Lecture 68 Lab - Microsoft Fabric data warehouse - SQL - Finding duplicate values
Lecture 69 Lab - Microsoft Fabric data warehouse - SQL- JOIN
Lecture 70 Lab - Microsoft Fabric data warehouse - SQL user-defined function
Section 4: Prepare Data - Microsoft Fabric - Lakehouse
Lecture 71 Section Code
Lecture 72 What is a Lakehouse
Lecture 73 Lab - Microsoft Fabric Lakehouse - Creating the Lakehouse
Lecture 74 Lab - Microsoft Fabric Lakehouse - Ingesting data via files
Lecture 75 Lab - Microsoft Fabric Lakehouse - Ingesting data via parquet files
Lecture 76 Microsoft Fabric Lakehouse - Delta Lake
Lecture 77 Lab - Microsoft Fabric Lakehouse - Ingesting data - Data pipeline
Lecture 78 Lab - Microsoft Fabric Lakehouse - Ingesting data - Data Flow Gen2
Lecture 79 Lab - Microsoft Fabric Lakehouse - Shortcuts - Azure Data Lake
Lecture 80 Lab - Microsoft Fabric Lakehouse - Shortcuts - AWS S3
Lecture 81 About using Apache Spark on Microsoft Fabric
Lecture 82 Lab - Microsoft Fabric Apache Spark - Creating a notebook
Lecture 83 Lab - Microsoft Fabric Apache Spark - Loading data into a Dataframe
Lecture 84 Lab - Microsoft Fabric Apache Spark - Performing operations on the data frame
Lecture 85 Lab - Microsoft Fabric Apache Spark - Saving the data frame
Lecture 86 Lab - Microsoft Fabric Apache Spark - Further working with data
Lecture 87 Microsoft Fabric Apache Spark - Running SQL commands in the notebook
Section 5: Practice Tests
This course is for students who want to prepare and take the DP-600 exam.,This course is for students who want to learn to use the Microsoft Fabric service.,This course will also help students learn to build semantic models in Power BI desktop.


Homepage:

https://www.udemy.com/course/dp-600-fabric-analytics-engineer-associate/