Microsoft Fabric: The Ultimate Guide
Microsoft Fabric: The Ultimate Guide
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Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.08 GB | Duration: 12h 35m
Warehouses, Lakehouses, Data Pipelines, Semantic Models, Power BI, Real Time Intelligence and more! (DP-600)
What you'll learn
Data Warehousing: Understand the principles of data warehousing, master SQL for querying and managing data, and learn how to design and implement data warehouse
Data Engineering: Develop robust data engineering pipelines using Spark (PySpark), manage large-scale data transformations, and automate workflows efficiently.
Data Factory: Master the use of Microsoft's Data Factory for orchestrating and automating data movement and transformation.
Real-Time Intelligence: Leverage real-time data processing capabilities to gain instant insights and act swiftly in dynamic business environments.
Power BI: Create powerful, interactive reports and dashboards.
A comprehensive end-to-end understanding of Microsoft Fabric
Requirements
Azure account and Microsoft Fabric Free Trial
Description
** This course can be used as supplementary preparation for the DP-600 Microsoft Fabric Analytics Engineer exam**Mastering Microsoft Fabric is your ticket to staying ahead in today's data-driven world. With data skills in high demand, learning this all-in-one platform will set you apart in the job market. From automating data processes to creating real-time insights, Microsoft Fabric equips you with the cutting-edge tools needed by top employers. Whether you're looking to boost your career or lead your companies data strategy, becoming proficient in Microsoft Fabric is a game-changer. Don't miss out on the opportunity to become an in-demand expert in the fast-growing field of data analytics and engineering.This course offers a balanced mix of theory and practical application. You'll dive deep into the concepts behind each component of Microsoft Fabric, followed by hands-on walkthroughs that allow you to apply what you've learned. The multi-experience course projects will challenge you to integrate your knowledge across different Fabric tools, preparing you to handle real-world scenarios with confidence.What You'll Learn:Data Warehousing: Understand the principles of data warehousing, master SQL for querying and managing data, and learn how to design and implement data warehouses within Microsoft Fabric.Power BI: Create powerful, interactive reports and dashboards.Data Engineering: Develop robust data engineering pipelines using Spark (PySpark), manage large-scale data transformations, and automate workflows efficiently.Data Factory: Master the use of Microsoft's Data Factory for orchestrating and automating data movement and transformation.Real-Time Intelligence: Leverage real-time data processing capabilities to gain instant insights and act swiftly in dynamic business environments.Course Features:Theory Lectures: Grasp the foundational concepts and methodologies behind each component of Microsoft Fabric.Hands-On Walkthroughs: Apply your learning in real-time with detailed, step-by-step walkthroughs of key tools and features.Multi-Experience Projects: Engage in comprehensive projects that require you to integrate multiple Fabric experiences, simulating real-world business challenges.By the end of this course, you will be proficient in using Microsoft Fabric to design, build, and manage comprehensive data solutions. Whether you're a data engineer, analyst, or business intelligence professional, this course will equip you with the skills needed become an expert with Microsoft Fabric.
Overview
Section 1: Introduction
Lecture 1 Welcome to the Course
Lecture 2 What is Microsoft Fabric?
Lecture 3 What is Microsoft Azure?
Lecture 4 Azure Account Set Up
Lecture 5 Azure Portal Overview, Resource Hierarchy and Cost Management
Lecture 6 Starting Free Trial on Fabric Using Personal Domain
Lecture 7 Starting Free Trial on Fabric Using Business Domain
Lecture 8 Fabric UI Overview
Lecture 9 Creating a Resource Group and ADLS Gen 2 Storage Account
Lecture 10 Parquet and Delta File Formats
Section 2: Data Warehousing and Power BI
Lecture 11 Section Overview
Lecture 12 Overview of Data Warehouses in Fabric
Lecture 13 Creating a Fabric Workspace for this Section
Lecture 14 Creating a Data Warehouse
Lecture 15 Overview of SQL Queries
Lecture 16 Adding Comments in your SQL Queries
Lecture 17 Message for Students with SQL Experience
Lecture 18 SQL Code used in this Section
Lecture 19 Create and Drop Schemas
Lecture 20 Data Types
Lecture 21 Create and Drop Tables
Lecture 22 Inserting Records into a Table (and first look at the Select Statement)
Lecture 23 Loading the Retail Dataset
Lecture 24 The Select Statement
Lecture 25 Selecting Distinct Records
Lecture 26 Functions and Expressions
Lecture 27 Ordering and Limiting your Results
Lecture 28 Filtering Records
Lecture 29 Grouping and Aggregating
Lecture 30 Joining Tables
Lecture 31 SQL Execution Order
Lecture 32 Create Table As Select
Lecture 33 Updating and Deleting Records
Lecture 34 Subqueries
Lecture 35 Views
Lecture 36 Visual Query Editor
Lecture 37 Zero Copy Clones and Time Travel
Lecture 38 Cross Warehouse Querying
Lecture 39 Query Monitoring
Lecture 40 Stored Procedures
Lecture 41 (Optional) Mirroring in Fabric - Snowflake Demo
Lecture 42 Semantic Modelling and Power BI
Lecture 43 Establishing Relationships in our Data Model
Lecture 44 Measures
Lecture 45 Preparing the Presentation Layer and Semantic Model
Lecture 46 Creating the Power BI Report
Lecture 47 Dashboards
Lecture 48 Apps
Section 3: Data Factory
Lecture 49 Section Overview
Lecture 50 Creating the Workspace for this Section
Lecture 51 Creating the Lakehouse for this Section
Lecture 52 Pipelines Overview
Lecture 53 Adding the Citibike Data to our Lakehouse
Lecture 54 Copy Data - Lakehouse Files
Lecture 55 Copy Data - Copy Behaviour
Lecture 56 Copy Data - Tables
Lecture 57 Copy Data - External Storage (ADLS Gen2)
Lecture 58 Lookup Activity
Lecture 59 Get Metadata Activity
Lecture 60 Dynamic Content and Expressions
Lecture 61 Parameters
Lecture 62 Variables
Lecture 63 ForEach Activity
Lecture 64 Switch Activity
Lecture 65 Invoke Pipeline Activity
Lecture 66 Dataflows Gen2
Lecture 67 Script Activity
Lecture 68 Stored Procedure Activity
Lecture 69 Scheduling
Section 4: Multi Experience Data Analyst/BI Engineering Project
Lecture 70 NYC Taxi Data Project: Overview and Solution Architecture
Lecture 71 Overview of NYC Taxi Data
Lecture 72 Creating the Data Lakehouse for Initital Data Storage
Lecture 73 Data Pipeline for Ingestion to Staging
Lecture 74 Dataflow Gen2 for Processing to Presentation
Lecture 75 End to End Pipeline Orchestration
Lecture 76 Power BI Reporting
Lecture 77 Replacing Dataflow Gen2 with a Stored Procedure
Section 5: Data Engineering
Lecture 78 Section Overview
Lecture 79 What is Apache Spark?
Lecture 80 Spark SQL and DataFrame API
Lecture 81 Creating the Workspace and Overview of the Spark Starter Pool
Lecture 82 Creating the Lakehouse for this Section
Lecture 83 Uploading the Retail Analytics Data Files
Lecture 84 Overview of Notebooks in Fabric
Lecture 85 Section Notebooks (Download and Import to Fabric)
Lecture 86 Adding Comments to Code Cells
Lecture 87 Built-In Functions and Modules
Lecture 88 Reading Parquet Files
Lecture 89 Reading CSV and JSON Files
Lecture 90 Specifying Schema using StructType and StructField
Lecture 91 Multi Line Strings
Lecture 92 Loading Files to DataFrames using the UI
Lecture 93 SQL Limitations in Spark
Lecture 94 Selecting Columns from DataFrames
Lecture 95 Selecting Columns from DataFrames (Supplementary)
Lecture 96 Writing DataFrames to Files
Lecture 97 Writing to and Reading DataFrames from Tables
Lecture 98 Adding, Updating and Removing DataFrame Columns
Lecture 99 Changing Data Types
Lecture 100 Renaming DataFrame Columns
Lecture 101 Filering Rows
Lecture 102 Sorting and Limiting
Lecture 103 Grouping and Aggregating
Lecture 104 Joining Data
Lecture 105 Union and Drop Duplicates
Lecture 106 SQL
Lecture 107 Temporary Views
Lecture 108 Shortcuts
Lecture 109 Creating Spark DataFrames from Python Data Structures
Lecture 110 Notebook Orchestration and Parameters
Lecture 111 Overview of Medallion Architecture
Lecture 112 Medallion Architecture Implementation
Lecture 113 Custom Spark Pools
Lecture 114 Environments in Microsoft Fabric
Section 6: Real Time Intelligence
Lecture 115 Section Overview
Lecture 116 Overview of Real Time Intelligence
Lecture 117 Creating the Workspace and Lakehouse for this Section
Lecture 118 Eventstream to Lakehouse
Lecture 119 Eventhouses, KQL Databases and KQL Querysets
Lecture 120 Eventstream to KQL Database
Lecture 121 Real Time Analysis and Dashboards
Lecture 122 Reflexes (Data Activator)
Lecture 123 Reflexes for Power BI Alerts
Lecture 124 Deleting the Workspace
Section 7: Multi Experience Data Engineering Project
Lecture 125 Project Overview and Solution Architecture
Lecture 126 Project Workspace and Lakehouse Creation
Lecture 127 Creating the ADLS Gen2 Container and Lakehouse Shortcut
Lecture 128 Assigning Storage Blob Data Contributor Access
Lecture 129 TLC Trip Record Data
Lecture 130 Creating the Medallion Schemas and Silver Lookup Table
Lecture 131 Overview of Data Processing Notebooks
Lecture 132 Creating the Orchestration Pipeline
Lecture 133 End to End Pipeline Run
Lecture 134 Automated Reflex File Arrival Trigger (Data Activator)
Lecture 135 Further Analysis
Section 8: Congratulations
Lecture 136 Bonus Lecture
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