Free Download Learn Microsoft Fabric Basic To Advance With Practical
Published 6/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.90 GB | Duration: 7h 21m
Microsoft Fabric End to End Analytics, Data engineering with Fabric, Certification, Real time analytics Fabric tutorial
What you’ll learn
Microsoft Fabric Fundamentals
Explore end-to-end analytics with Microsoft Fabric
Master the Microsoft Fabric Lakehouse
Use Apache Spark in Microsoft Fabric
Work with Delta Lake tables in Microsoft Fabric
Master Data Factory pipelines in Microsoft Fabric
Learn data warehouses in Microsoft Fabric
Data with Dataflows Gen2 in Microsoft Fabric
Master Real-Time Analytics in Microsoft Fabric
Learn data science in Microsoft Fabric
Learn Microsoft Fabric with end to end project idea
Learn Microsoft Fabric with practical
Requirements
Anyone can take up this course
Description
Welcome to the comprehensive course on Microsoft Fabric! In this course, you will embark on a journey from the basics to advanced concepts, gaining practical knowledge and skills that will empower you in the realm of data science, data engineering, and real-time data analytics. With a strong focus on Microsoft Fabric, this course provides you with the tools and techniques to leverage the power of Fabric for end-to-end analytics.Throughout the course, you will delve into the world of data engineering, learning how to efficiently transform, process, and analyze vast amounts of data using Microsoft Fabric. You will explore various data engineering techniques, including data warehousing, data pipelines using Data Factory, and parallel processing with Apache Spark. Gain hands-on experience as you navigate real-world scenarios and challenges, equipping you with the expertise to tackle complex data engineering projects.Moreover, this course takes you on an exploration of the art of data science using Microsoft Fabric. Learn how to harness the potential of Fabric to perform advanced analytics, uncover valuable insights, and make data-driven decisions. Dive into topics such as real-time data analytics, where you will discover how to process and analyze streaming data in real time, enabling you to gain immediate insights and take action when it matters most.In addition, you will discover the power of Power BI as a visualization and reporting tool, enabling you to create interactive and visually compelling dashboards that communicate insights effectively. Through hands-on exercises, you will learn how to create compelling visualizations, share reports, and collaborate with others using Power BI.This course also offers guidance on obtaining a Microsoft Fabric certification, helping you demonstrate your expertise and proficiency in Microsoft Fabric to potential employers or clients. You will gain insights into the certification process, learn valuable exam tips, and understand the areas of focus required to excel in the certification exams.By the end of this course, you will have acquired a solid foundation in Microsoft Fabric, equipped with the knowledge and skills to tackle data engineering, real-time data analytics, and data science projects with confidence. Whether you are an aspiring data scientist, data engineer, or analytics professional, this course is designed to propel your career forward by providing you with the essential skills needed in today’s data-driven world.Enroll now and embark on your journey to become a Microsoft Fabric expert!
Overview
Section 1: Introduction
Lecture 1 Setup Account with Microsoft Fabric
Lecture 2 Walkthrough with Features of Microsoft Fabric
Lecture 3 Microsoft Fabric Architecture
Section 2: Lakehouse
Lecture 4 Introduction to Lakehouse, OneLake
Lecture 5 Setup your first Lakehouse & Ingest Data
Lecture 6 Delta format tables
Lecture 7 SQL Endpoints
Lecture 8 Data Visualization in Spark Notebook
Lecture 9 Visual Query Editor
Lecture 10 Create Report
Section 3: Data Processing with Apache Spark
Lecture 11 Introduction to Large Scale Data Analytics
Lecture 12 Apache Spark
Lecture 13 Spark Settings in Microsoft Fabric
Lecture 14 Setup your first Notebook
Lecture 15 DataFrame from Lakehouse
Lecture 16 Data Transformation, Saving the Transformed Data and Partitioning using PySpark
Lecture 17 Parquet File, Partitioning in Spark RDD
Section 4: Delta Tables in Microsoft Fabric
Lecture 18 Load Data into Spark Dataframe
Lecture 19 Managed and External Tables
Lecture 20 Data Insertion in Delta Table
Lecture 21 Table Updation and Table Versioning
Lecture 22 Create Delta Table from Streaming Data
Section 5: Data Pipelines in Microsoft Fabric
Lecture 23 SparkSQL API to process data
Lecture 24 ETL (Extract, Transfer and Load)
Lecture 25 Pipeline: Copy Data Activity, Delete Data Activity and Notebook Activity
Lecture 26 Variable in Pipeline
Lecture 27 Run and Monitor Pipeline
Section 6: Ingest Data with Dataflow (gen2)
Lecture 28 Copy Data, Transform Data using Dataflow
Section 7: Data Warehousing in Microsoft Fabric
Lecture 29 Introduction to Data Warehouse
Lecture 30 Dimensional Modelling in Data Warehouse
Lecture 31 Setup your Data Warehouse in MS Fabric
Lecture 32 Query your Data Warehouse
Lecture 33 Visual Query Editor in Data Warehouse
Lecture 34 Performance Monitoring in Warehouse
Section 8: Real Time Data Analytics
Lecture 35 Introduction to Real time Data Analytics
Lecture 36 Setup your KQL Database
Lecture 37 Data Processing and Analysis using KQL QuerySet
Lecture 38 Data Visualization
Section 9: Data Science with Microsoft Fabric
Lecture 39 Introduction to Data Science, Predictive Analytics and Machine Learning
Lecture 40 Notebook, Experiment and Run
Lecture 41 Setup and load data into Notebook
Lecture 42 Create Experiment and Build your Model
Lecture 43 Compare an Save your Models
Anyone who is interested in Data Field,Aspiring to get job as Azure Data Engineer,Aspiring to work as Azure Data Scientist,Anyone who is looking forward to start his career as a Azure Data Engineer,Anyone who is looking forward to start his career as a Azure Data warehouse specialist,Anyone who is looking forward to start his career as a Data analyst
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