Microsoft Fabric A Deeper Dive

Microsoft Fabric – A Deeper Dive, available at $79.99, has an average rating of 4.42, with 76 lectures, based on 363 reviews, and has 3828 subscribers.

You will learn about Power BI with DirectLake. A 170 million row fact table is used to demonstrate we dont need import mode any more! Apache Spark Integration into Microsoft Fabric Data science in Microsoft Fabric attempting to predict how long a taxi ride in New York City might take Ingesting data using the power and flexibility of data pipelines with DataFlows Gen2 and Data Factory Building a data warehouse in Microsoft Fabric Building a real-time analytics solution using New York City taxi data and Event Streams with KQL Semantic Link for Power BI This course is ideal for individuals who are This is an intermediate level course on Microsoft Fabric. Some Fabric experience, or having taken another Microsoft Fabric introductory course, might be helpful It is particularly useful for This is an intermediate level course on Microsoft Fabric. Some Fabric experience, or having taken another Microsoft Fabric introductory course, might be helpful.

Enroll now: Microsoft Fabric – A Deeper Dive

Summary

Title: Microsoft Fabric – A Deeper Dive

Price: $79.99

Average Rating: 4.42

Number of Lectures: 76

Number of Published Lectures: 76

Number of Curriculum Items: 76

Number of Published Curriculum Objects: 76

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Power BI with DirectLake. A 170 million row fact table is used to demonstrate we dont need import mode any more!

Apache Spark Integration into Microsoft Fabric

Data science in Microsoft Fabric attempting to predict how long a taxi ride in New York City might take

Ingesting data using the power and flexibility of data pipelines with DataFlows Gen2 and Data Factory

Building a data warehouse in Microsoft Fabric

Building a real-time analytics solution using New York City taxi data and Event Streams with KQL

Semantic Link for Power BI

Who Should Attend

This is an intermediate level course on Microsoft Fabric. Some Fabric experience, or having taken another Microsoft Fabric introductory course, might be helpful

Target Audiences

This is an intermediate level course on Microsoft Fabric. Some Fabric experience, or having taken another Microsoft Fabric introductory course, might be helpful

A deeper dive into what you might ask? A deeper dive than what our initial Microsoft Fabric course covers. We go more deeply into data engineering, data science, data warehousing, Spark, Power BI with DirectLake, Power BI with Semantic Link with end-to-end examples and studies.

If you are a Power BI developer, you will love our deep dive into DirectLake where we use a 170 million row fact table to show that DirectLake is every bit as fast as tabular import mode. Hard to believe but true. We also cover Semantic Link with Power BI allowing Spark notebooks to interact with Power BI datasets.

If data engineering is your specialty we go through and end-to-end project demonstrating how to use Dataflows Gen2 and Data Factory Copy Activity, with pipelines to build an ingestion process.

If your interest is data science we go through an end-to-end machine learning project to demonstrate how Fabric and notebooks can be used or predict how long a taxi ride might take in New York City.

If you have a need to learn more about real-time analytics and KQL, we go through a project where we simulate taxi data being ingested using event streams and KQL.

If you are interested in building a data warehouse, we have an end-to-end data warehouse project showing how this can be done in Microsoft Fabric.

Interested in Apache Spark? We cover the important areas of Spark and how it integrates into Microsoft Fabric.

By the time you complete this 10+ hour course you will feel completely comfortable using all the most commonly used experiences in Microsoft Fabric.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Microsoft Fabric is Generally Available!

Lecture 3: Exercises and Quizzes in this Course – Please Watch!

Lecture 4: Getting Started with Microsoft Fabric

Chapter 2: Direct Lake and Power BI

Lecture 1: Overview – Part 1

Lecture 2: Overview – Part 2

Lecture 3: XMLA-Write Support

Lecture 4: Putting Direct Lake to the Test – Part 1

Lecture 5: Putting Direct Lake to the Test – Part 2

Lecture 6: Power BI Desktop and Direct Lake

Lecture 7: On-Demand Loading

Lecture 8: Default Semantic Model vs. Custom Model

Chapter 3: Data Science in Microsoft Fabric

Lecture 1: Introduction to Data Science

Lecture 2: Data Science in Microsoft Fabric

Lecture 3: Notebooks

Lecture 4: Experiments

Lecture 5: Models

Lecture 6: Preparing Data – Data Wrangling

Lecture 7: End-to-End Project: Getting Set Up

Lecture 8: End-to-End Project: Ingesting Data

Lecture 9: End-to-End Project: Exploring the Data Part 1

Lecture 10: End-to-End Project: Exploring the Data Part 2

Lecture 11: End-to-End Project: Exploring the Data Part 3

Lecture 12: End-to-End Project: Exploring the Data Part 4

Lecture 13: End-to-End Project: Train and Evaluate the Data Part 1

Lecture 14: End-to-End Project: Train and Evaluate the Data Part 2

Lecture 15: End-to-End Project: Train and Evaluate the Data Part 3

Lecture 16: End-to-End Project: Train and Evaluate the Data Part 4

Lecture 17: End-to-End Project: Reporting Part 1

Lecture 18: End-to-End Project: Reporting Part 2

Chapter 4: Real-Time Analytics in Microsoft Fabric

Lecture 1: Introduction to Real-Time Analytics in Microsoft Fabric

Lecture 2: Event Stream

Lecture 3: Creating a KQL Database

Lecture 4: Creating an Event Stream

Lecture 5: Getting Location Data

Lecture 6: Adding the Data to the Lakehouse

Lecture 7: Exploring the Data

Lecture 8: More Data Exploration

Lecture 9: Real-Time Analytics becomes Real-Time Intelligence

Chapter 5: Data Factory in Microsoft Fabric

Lecture 1: Introduction to Data Factory in Microsoft Fabric

Lecture 2: Building a Pipeline – Part 1

Lecture 3: Building a Pipeline – Part 2

Lecture 4: Building a Pipeline – Part 3

Lecture 5: Building a Pipeline – Part 4

Lecture 6: Building a Pipeline – Part 5

Chapter 6: Data Warehouse in Microsoft Fabric

Lecture 1: Introduction to the Microsoft Fabric Data Warehouse

Lecture 2: Building a Data Warehouse – Part 1

Lecture 3: Building a Data Warehouse – Part 2

Lecture 4: Building a Data Warehouse – Part 3

Lecture 5: Building a Data Warehouse – Visual Query Builder

Lecture 6: Using Shortcuts to Analyze Data in a Lakehouse

Lecture 7: Modeling the Data and Auto-Generating a Power BI Report

Chapter 7: Apache Spark in Microsoft Fabric

Lecture 1: Introduction to Apache Spark in Fabric

Lecture 2: Spark Libraries

Lecture 3: Dataframe Basics – Part 1

Lecture 4: Dataframe Basics – Part 2

Lecture 5: Dataframe Basics – Part 3

Lecture 6: Common Operations with Dataframes

Lecture 7: Filtering Data

Lecture 8: Aggregating Data

Lecture 9: Joining Dataframes

Lecture 10: Working with Dates

Lecture 11: SQL Statements and Spark

Lecture 12: Machine Learning

Lecture 13: Microsoft Fabric 1.1. / Spark Runtime

Lecture 14: Spark Configuration

Lecture 15: Spark Autotuning

Chapter 8: Miscellaneous Topics

Lecture 1: Semantic Link for Power BI – Part 1

Lecture 2: Semantic Link for Power BI – Part 2

Lecture 3: Semantic Link for Power BI – Part 3

Lecture 4: Data Activator – Part 1

Lecture 5: Data Activator – Part 2

Lecture 6: Microsoft Fabric Licensing and Pricing

Lecture 7: Microsoft Fabric Licensing and Pricing July 2024 Update

Chapter 9: Bonus

Lecture 1: Bonus Offer

Lecture 2: DP-600 Exam

Instructors

Randy Minder
Lead BI Developer / Power BI / Microsoft Fabric

Rating Distribution

1 stars: 5 votes

2 stars: 8 votes

3 stars: 33 votes

4 stars: 128 votes

5 stars: 189 votes

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