DP-600: Implement Analytics Solutions using Microsoft Fabric

DP-600: Implement Analytics Solutions using Microsoft Fabric, available at $44.99, has an average rating of 4.63, with 123 lectures, 24 quizzes, based on 167 reviews, and has 1949 subscribers.

You will learn about Plan, implement, and manage a solution for data analytics Prepare and serve data Implement and manage semantic models Explore and analyze data This course is ideal for individuals who are This course is for you if you want to implement or manage advanced Power BI skills, and load data into and manipulate data in Fabric lakehouses and warehouseslakehouses or You could be a data analyst, and want to expand your skills to become a Fabric analytics engineer. or By the end of this course, after entering the official Practice Tests, you could enter (and hopefully pass) Microsoft's official DP-600 exam. or Wouldn't the "Implementing Analytics Solutions Using Microsoft Fabric" certification look good on your CV or resume? It is particularly useful for This course is for you if you want to implement or manage advanced Power BI skills, and load data into and manipulate data in Fabric lakehouses and warehouseslakehouses or You could be a data analyst, and want to expand your skills to become a Fabric analytics engineer. or By the end of this course, after entering the official Practice Tests, you could enter (and hopefully pass) Microsoft's official DP-600 exam. or Wouldn't the "Implementing Analytics Solutions Using Microsoft Fabric" certification look good on your CV or resume?.

Enroll now: DP-600: Implement Analytics Solutions using Microsoft Fabric

Summary

Title: DP-600: Implement Analytics Solutions using Microsoft Fabric

Price: $44.99

Average Rating: 4.63

Number of Lectures: 123

Number of Quizzes: 24

Number of Published Lectures: 123

Number of Published Quizzes: 24

Number of Curriculum Items: 147

Number of Published Curriculum Objects: 147

Number of Practice Tests: 2

Number of Published Practice Tests: 2

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Plan, implement, and manage a solution for data analytics
Prepare and serve data
Implement and manage semantic models
Explore and analyze data

Who Should Attend

This course is for you if you want to implement or manage advanced Power BI skills, and load data into and manipulate data in Fabric lakehouses and warehouseslakehouses
You could be a data analyst, and want to expand your skills to become a Fabric analytics engineer.
By the end of this course, after entering the official Practice Tests, you could enter (and hopefully pass) Microsoft's official DP-600 exam.
Wouldn't the "Implementing Analytics Solutions Using Microsoft Fabric" certification look good on your CV or resume?

Target Audiences

This course is for you if you want to implement or manage advanced Power BI skills, and load data into and manipulate data in Fabric lakehouses and warehouseslakehouses
You could be a data analyst, and want to expand your skills to become a Fabric analytics engineer.
By the end of this course, after entering the official Practice Tests, you could enter (and hopefully pass) Microsoft's official DP-600 exam.
Wouldn't the "Implementing Analytics Solutions Using Microsoft Fabric" certification look good on your CV or resume?

This course covers the additional content required for the DP-600 certification exam, building on your existing knowledge gained for the PL-300 exam. It is as per the DP-600 requirements as of 22 July 2024.

It comes in two parts – additional Power BI knowledge, and Fabric.

In Part 1 of this course, we’ll start with Power BI. We’ll look at:

Developing our design of semantic models, including calculation groups/items and field parameters.
Expanding our DAX knowledge, with DAX variables and windowing functions.
Using external apps, such as Tableau Editor 2 and DAX Studio,
Implementing many-to-many relationships, implementing dynamic strings, and using the Optimize menu.
The analytics development lifecycle, focusing on version control and deployment solutions,
Other Analytics topics, such as creating aggregation tables and using the XMLA endpoint.

In Part 2 of this course, we’ll look at other Fabric apps which can be used by data analytics in conjunction with Fabric.

After a brief look around Fabric, we’ll start by ingesting data by using data pipelines and dataflows.
We’ll then create a lakehouse and use notebooks to load data, manipulate it in both SQL and PySpark, and save the resulting dataframes in PySpark. We’ll then use our SQL knowledge in a data warehouse.
Finally, we’ll create additional objects such as shortcuts and partitions, and optimize performance, implement Slowly Changing Dimensions, and manage our Fabric capacity.

Prior knowledge of all of the topics in the PL-300 exam is assumed, especially with regards to DAX functions. This content is available in “PL-300 certification: Microsoft Power BI Data Analyst”, which is available on Udemy.

Prior knowledge of SQL Server would be helpful, but is not essential.

Once you have completed the course, you will have a good knowledge of implementing a solution for data analytics, preparing and serving data, implementing and managing semantic models, and exploring and analyzing data. And with some practice, you could even go for the official Microsoft certification DP-600 – wouldn’t that look good on your CV or resume?

I hope to see you in the course – why not have a look at what you could learn?

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Welcome to Udemy

Lecture 3: The Udemy Interface

Lecture 4: Do you want auto-translated subtitles in more languages?

Lecture 5: What are we going to learn?

Lecture 6: Resources

Lecture 7: Saved Power BI files

Chapter 2: Part 1 Level 1: Design and build semantic models

Lecture 1: Creating semantic model

Lecture 2: 29. 1st Normal form

Lecture 3: 29. 2nd and 3rd Normal form

Lecture 4: 27, 40. Implementing a star schema for a semantic model

Lecture 5: Practice Activity Number 1

Lecture 6: Practice Activity Number 1 – The Solution

Chapter 3: Part 1 Level 2: Calculation groups/items, field parameters, and custom theme

Lecture 1: 43a. Enabling the calculation groups preview feature

Lecture 2: 43a. Creating our first calculation group and item

Lecture 3: 43a. Adding additional calculation items

Lecture 4: 43a, 43b. Using our calculation group, including dynamic strings

Lecture 5: 43c. Implement field parameters

Lecture 6: 4. Create a custom Power BI report theme

Lecture 7: Practice Activity Number 2

Lecture 8: Practice Activity Number 2 – The Solution

Chapter 4: Part 1 Level 3: DAX functions

Lecture 1: 42a. Using DAX variables

Lecture 2: 42d. DAX Windowing functions: ROWNUMBER

Lecture 3: 42d. DAX Windowing functions: RANK

Lecture 4: 42d. DAX Windowing functions: INDEX

Lecture 5: 42d. DAX Windowing functions: OFFSET

Lecture 6: 42d. DAX Windowing functions: WINDOW

Lecture 7: Practice Activity Number 3

Lecture 8: Practice Activity Number 3 – The Solution

Chapter 5: Part 1 Level 4: Tabular Editor 2 and DAX Studio

Lecture 1: 39. Identify use cases for DAX Studio and Tabular Editor 2 (TE2), installing TE2

Lecture 2: 50. Optimize a semantic model by using Tabular Editor 2 (BPA)

Lecture 3: 46. Implement object-level security (OLS)

Lecture 4: 49. Improve DAX performance by using DAX Studio

Lecture 5: 49. Using the VertiPaq Analyzer

Lecture 6: ALM Toolkit

Lecture 7: Translating metadata

Chapter 6: Part 1 Level 5: Relationships and performance improvements

Lecture 1: 41. Resolve many-to-many relationships – Joint Bank Accounts

Lecture 2: 43b. Implement dynamic strings

Lecture 3: 41. Resolve many-to-many relationships – creating a Bridge Table

Lecture 4: 48. The Optimize menu

Chapter 7: Part 1 Level 6: Manage the analytics development lifecycle

Lecture 1: 10. Creating a Premium Per User (PPU) workspace and Azure DevOps repos

Lecture 2: 10. Implement version control for a workspace

Lecture 3: 11. Create and manage a Power BI Desktop project (.pbip)

Lecture 4: 12. Plan and implement deployment solutions

Lecture 5: 12. Managing deployment solutions

Chapter 8: Part 1 Level 7: Other Power BI Analytics topics

Lecture 1: 44. Design and build a large format semantic models

Lecture 2: 13. Perform impact analysis of downstream dependencies

Lecture 3: 14. Deploy and manage semantic models by using the XMLA endpoint

Lecture 4: 15a. Creating and updating Power BI template (.pbit) files

Lecture 5: 15b. Creating and updating Power BI data source (.pbids) files

Lecture 6: 15c. Creating and updating shared semantic models

Lecture 7: 45. Create an Azure SQL Database, and Design and build a composite model

Lecture 8: 45. Adding aggregations

Chapter 9: Part 1 – Practice Test for advanced Power BI semantic models

Chapter 10: Part 2 Section 1 – A look around Fabric

Lecture 1: 8. Creating a Fabric capacity and configure Fabric-enabled workspace settings

Lecture 2: 1, 9. Identify requirements for a Fabric solution and manage Fabric capacity

Lecture 3: A quick tour of Fabric

Chapter 11: Part 2 Section 2 – Using data pipelines and dataflows

Lecture 1: 16b, 22b. Ingest data by using a dataflow

Lecture 2: 16b, 22b. Add a destination to a dataflow

Lecture 3: 25a. Saving as a template and scheduling a dataflow

Lecture 4: 16a, 23. Ingest data by using a data pipeline, and adding other activities

Lecture 5: 22a. Copy data by using a data pipeline

Lecture 6: 24. Schedule data pipelines and monitor data pipeline runs

Lecture 7: Exploring sample data (including copy data assistant) + data pipeline templates

Lecture 8: 22d. Implement Fast Copy when using dataflows

Lecture 9: Practice Activity Number 4

Lecture 10: Practice Activity Number 4 – The Solution

Chapter 12: Part 2 Section 3 – Loading and saving data using notebooks

Lecture 1: 21. Ingesting data into a lakehouse using a local upload

Lecture 2: 21. Choose an appropriate method for copying to a Lakehouse or Warehouse

Lecture 3: 16c, 22c. Ingesting data using a notebook, and copying to a table

Lecture 4: 16c, 22c. Saving data to a file or Lakehouse table

Lecture 5: Loading data from a table in PySpark and SQL, and manipulating the results

Lecture 6: Practice Activity Number 5

Lecture 7: Practice Activity Number 5 – The Solution

Chapter 13: Part 2 Section 4 – Manipulating dataframes – choosing columns and rows

Lecture 1: Reducing the number of columns shown

Lecture 2: 34. Filtering data with: where, limit and tail

Instructors

Phillip Burton
Best Selling Instructor – over 800,000 students so far
I Do Data Limited
Improve your skills in SQL, Office, Tableau, Power BI + more

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 7 votes
4 stars: 68 votes
5 stars: 91 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu