Microsoft Fabric Complete Guide - Future Of Data With Fabric
Published 10/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.27 GB | Duration: 9h 0m

Microsoft Fabric Masterclass | Data Factory, Warehouse, Data Science, Power BI all in Fabric | Learn Microsoft Fabric

What you'll learn
Understand Microsoft Fabric, what it is, how it works and its various components
Learn how to explore, create, assign and configure workspaces
Discover the principles of data engineering in Microsoft Fabric, including Lakehouse and Delta Lake
Explore the application of OneLake on Fabric
Learn about data loading and ingestion options in the Fabric enviroment
Understand the connection of Power BI and Fabric in data visualization
Discover how to use data factory to create and execute data pipelines in Fabric
Find out the uses of Fabric within the domains of data science and data engineering
Gain comprehensive understanding of performance management, SQL, and KQL, and learn how to use KSQL Queryset, KSQL database, and KSQLMagic for data analysis.
Explore how to manage access control, governance, and monitoring in the Fabric environment
Requirements
Basic understanding and knowledge of data concepts and terminologies.
Programming experience and familiarity with data engineering and data science languages such as SQL, Spark and Python is not required, but recommend
Simple understanding of cloud computing concepts and services, particularly for Microsoft Azure.
Description
Are you ready to immerse yourself in the cutting-edge world of Microsoft Fabric and revolutionize your data-professional and data engineering skills? This in-depth course will take you on an exploration of the power of Microsoft Fabric, Microsoft's cutting-edge data tools and analytics platform. With over 9 hours of engaging content, you will obtain a solid grasp of Microsoft Fabric's capabilities and how it can assist you with your data journey.In this comprehensive Microsoft Fabric course, you will learn about important topics like Lakehouse versus warehouse and the concept of workspaces. Learn how to set up and configure workspace access, how to use OneLake and Delta Lake, and how to apply authentication and authorization techniques for data protection. Improve your knowledge of shortcuts, monitoring hubs, and data hubs. Learn about Spark integration, different ingest strategies for efficient data loading, and key topics like SQL vs. KQL and performance management.Whether you're a seasoned data expert or just starting out, this course will prepare you to thrive in the world of data.What is this course all about?The main goal of this course is to offer a comprehensive guide to Microsoft Fabric and showcase its diverse applications across multiple domains in the data field. By delving into data engineering, data science, and data analytics, you will develop a holistic comprehension of how Microsoft Fabric can be effectively utilized in the world of data. What is Microsoft Fabric?Microsoft Fabric is an all-in-one cloud-based analytics platform that includes data migration, data lakes, data engineering, data integration, data science, real-time analytics, and business intelligence. It offers a user-friendly, cloud SaaS interface that makes it accessible even to people with limited data analytics knowledge. All analytics components are available on a single platform, easing data pipeline management, model deployment, and insight sharing.Who are the instructors for this course?Sawyer NyquistA data professional from West Michigan, USA, holding the position of Sr. Data Engineering Consultant at Microsoft. He specializes in business intelligence, data engineering, data warehousing, and data platform architecture. Possessing cloud data certifications in data engineering, Apache Spark, and business intelligence, he has collaborated with numerous companies to strategize and deploy data platforms, analytics, and technology and to foster growth.Hitesh GovindHitesh is a cloud solutions architect from Southern California, USA, with a wide expertise in database administration and enterprise architecture. He is also a published author who is passionate about mentoring teenagers and an entrepreneur who believes in the power of technology to tackle real-world business challenges. Hitesh also has expert-level certification in Azure Solutions Architecture, as well as Data Engineer and Power Platform certifications.Why learn Microsoft Fabric?Role-Tailored Tools: Microsoft Fabric provides specialized tools for different roles involved in the data analytics process, catering to the demands of data professionals, analysts, and engineers.Unified Platform: Microsoft Fabric unifies diverse components of an analytics solution into a single platform.Cloud-Based Accessibility: As a cloud-based platform, Fabric allows users to access it from anywhere, making it ideal for organizations with distributed teams or those requiring quick scalability for their analytics capabilities.AI-Powered Capabilities: Microsoft Fabric incorporates features like Copilot, which aids in efficient code writing, and Data Activator, which provides real-time data monitoring, enhancing data analysis and decision-making.Adaptation to Current Trends and Upskilling: Embracing Microsoft Fabric allows individuals and organizations to stay current with emerging trends in data analytics, providing opportunities for continuous learning and skill enhancement to remain competitive in the data realm.Why choose this course?Learn from Experts: The course is taught by industry experts who have extensive knowledge and experience in the fields of data science, data analytics, and data engineering.Comprehensive Coverage: This course provides a complete guide covering the areas of data engineering, data analytics, and data science, making it a useful and well-rounded resource for data professionals.Practical Approach: Going beyond theoretical explanations, we provide practical examples, allowing students to practice alongside the instructor, which allows the learners to apply the concepts in real-world scenarios, enhancing their learning experience.Instructor support: Whether you're stuck on a particular subject, seeking clarification, or looking for expert insights, our instructors are committed to helping you every step of the way.Course Overview:Sections 1: Learn about the course objectives, the instructors, and how to align analytical solutions with the needs of the clients.Section 2: An introduction to Microsoft Fabric along with workspace set-up and configuration.Sections 3 to 5: An overview of data engineering in Fabric, covering OneLake, Delta Lake, shortcuts, authentication process, and monitoring Spark jobs.Section 6: Introduction to data warehouse in Fabric covering data ingestion, data loading, performance management, etc.Section 7: Learn real-time analytics including SQL and KQL, monitoring queries and data, KSQLmagic along with Spark integration.Sections 8 and 9: Understanding data factory, data flows, pipelines and workspace set-up.Section 10: Exploring the integration of Power BI with Fabric.Section 11: Introduction to data science process, model management and practical exercises.Section 12: Covers the fundamentals of data management including access control, governance and security, and monitoring.
Overview
Section 1: Introduction
Lecture 1 Instructors Introduction
Lecture 2 Learning objectives
Lecture 3 Understanding the Objectives
Lecture 4 Success Criteria
Lecture 5 Introduction
Lecture 6 Course Roadmap
Section 2: Microsoft Fabric Foundation
Lecture 7 Overview of Microsoft Fabric
Lecture 8 Lakehouse vs Warehouse
Lecture 9 Fabric License Types
Lecture 10 Getting-Started: Sign-up Screen
Lecture 11 Concept of Workspaces
Lecture 12 Create and Configure Workspace Access
Lecture 13 Workspace Settings
Section 3: Data Engineering - OneLake
Lecture 14 Introduction to Data Engineering in Fabric
Lecture 15 Introduction to OneLake
Lecture 16 Lakehouse
Lecture 17 Delta Lake
Lecture 18 OneLake Explorer
Lecture 19 Authentication and Authorization
Lecture 20 Introduction to Shortcuts
Lecture 21 Creating Shortcuts
Lecture 22 Monitoring Hub and Data Hub
Section 4: Data Engineering - Lakehouse
Lecture 23 Introduction
Lecture 24 Architecture
Lecture 25 Distinctions between Lakehouse & Warehouse
Section 5: Data Engineering - ETL with Lakehouse
Lecture 26 What is Spark?
Lecture 27 Notebook Overview
Lecture 28 Web based and VS Code Notebooks
Lecture 29 Spark + Monitoring Spark Jobs
Section 6: Data Warehouse - Serverless Engine
Lecture 30 Warehouse-SQL Scripts
Lecture 31 Introduction
Lecture 32 Default Dataset and Modelling
Lecture 33 Ingest Methods
Lecture 34 Load Data Introduction
Lecture 35 Load Data into Lakehouse
Lecture 36 Load Data Using Data Pipeline Part 1
Lecture 37 Load Data Using Dataflows
Lecture 38 Load Data Using Data Pipeline Part 2
Lecture 39 Models and Power BI reports
Lecture 40 Cross-database Query
Lecture 41 Roles + Permissions (RLS, CLS)
Lecture 42 Manage Performance
Lecture 43 Warehouse-SQL Scripts
Section 7: Real-Time Analytics
Lecture 44 Real-Time Analytics - KQL Scripts
Lecture 45 SQL vs KQL Introduction
Lecture 46 Create, Process and Monitor
Lecture 47 KSQL Queryset
Lecture 48 KSQL Database
Lecture 49 KSQLmagic
Lecture 50 Spark
Lecture 51 Real-Time Analytics - KQL Scripts
Section 8: Data Factory Introduction
Lecture 52 What is Data Factory?
Lecture 53 Data Flows and Pipelines
Lecture 54 Architecture
Lecture 55 Workspace Setup
Section 9: Data Factory End-to-End Build
Lecture 56 Control Table and Copy Data
Lecture 57 Metadata Copy Pattern
Lecture 58 Script Activity
Lecture 59 Data Flows Gen2 Introduction
Lecture 60 Data Flows Gen2 Continuation
Lecture 61 Execute Pipeline
Lecture 62 Shortcut to Other Workspaces
Lecture 63 Notebooks
Lecture 64 Data Flow Gen2 Transformations
Lecture 65 Pipelines, Notebooks and Parameters
Lecture 66 Monitoring Notebooks in Pipelines
Section 10: Data Visualization with Power BI
Lecture 67 Power BI and Fabric
Lecture 68 Version Control
Lecture 69 Direct Lake
Section 11: Data Science
Lecture 70 Data Science - Resources
Lecture 71 What is Data Science?
Lecture 72 The Data Science Process
Lecture 73 Items and Models
Lecture 74 Excercise
Lecture 75 Saving Models
Lecture 76 Model Management
Lecture 77 Data Science - Resources
Section 12: Data Management
Lecture 78 Introduction
Lecture 79 Access Control
Lecture 80 Governance
Lecture 81 Monitoring
Citizen and professional data practioners,Data professionals working with data infrastructure, ETL, and data integration, who are seeking to learn how they can utilize Fabric in their data workflows,Business analysts who want to expand their knowledge and skills by learning about data engineering practices, data lakes, and the integration with Power BI for reports and visualization,Data scientists who are looking at how they can leverage Fabric in their data science projects, including model management and integration with Azure services

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