
This course includes our updated coding exercises so you can practice your skills as you learn.
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Explore how this DP-600 Fabric Analytics course designs, prepares, and manages data and semantic models in Power BI and Fabric, using SQL, KQL, and DAX.
Learn why Power BI and Fabric require a work or school email, and explore practical paths to obtain one, free Microsoft 365 Business Basic, and option to buy a domain.
Learn to load data from a Fabric data workbook and build a stacked column chart in Power BI. Save the report locally and publish it to the Power BI service.
Create calculated columns using basic operators to transform data, rename columns, and format currency in the table view, including converting amount from pounds to dollars and using date hierarchies.
Explore the logical functions false, true, and iferror, and the divide function in DAX to handle division by zero and return blanks or alternate values.
Practice activity 2 guides you to evolve your model with calculated columns such as location name, is us, and continent mapping, using logical functions and basic operators in fabric analytics.
Explore DAX statistical functions in Power BI for in-memory table manipulation, including add columns, count rows, distinct count, percentiles, and ranks with rank.eq and rank.x.
Demonstrates creating a calculated column and a measure to average processing fees by country with a switch, and ranks sales territories using rank.eq in a dim geography model.
Learn how information functions in DAX work, focusing on is error and if error to handle cascading errors, and on lookup value for single-value lookups with optional alternate results.
Explore how the filter function narrows a table expression to a specific context, such as year 2028, by creating a measure like amount 2028 from the fact finance table.
Explore practical DAX filter functions beyond the basics, including cross filter for single or bidirectional direction, distinct for unique values, and keep filters to combine nested calculate contexts.
Learn to use the USERELATIONSHIP function to activate an inactive relationship, apply the EDATE function to shift dates by months, and use CROSSFILTER to adjust bidirectional filtering.
Build a date-first-purchase visualization from the dim customer table, add measures such as year start, running total, prev year, and current month, and use a date table for relationships.
Identify bottlenecks with the Performance Analyzer and optimize queries, visuals, and DAX performance. Apply strategies to reduce granularity, limit visuals, and simplify models, including cross-filter direction and snowflake-to-star schema.
Learn how query folding improves Power BI query performance by pushing transformations to SQL Server via native queries, reducing data load and leveraging server-side operations.
Explore the Power BI service interface, publish and view semantic models and reports in your workspace, and learn to create, edit, and save dashboards and reports.
FactInternetSales, DimProduct, DimCategory and DimSubcategory
Implement a star schema for a Power BI semantic model, denormalizing from snowflake, using Power Query merge queries and left outer joins to optimize large datasets.
Demonstrates implementing a star schema in Power BI by building relationships, adding calculated columns using related, and visualizing sales by territory and year in a matrix.
Add and reorder calculation items to show total, year to date, quarter to date, month to date, and a year over year calculation using time intelligence in a matrix.
This course covers the content required for the DP-600 "Fabric Analytics Engineer Associate" certification exam.
It is as per the DP-600 requirements as of 15 November 2024, with some updates as of 14 January 2026 and 20 April 2026.
This course is also useful for the following Microsoft Applied Skills:
APL-3008 "Implement a Real-Time Intelligence solution with Microsoft Fabric"
APL-3010 "Implement a data warehouse in Microsoft Fabric"
Please note: This course is not affiliated with, endorsed by, or sponsored by Microsoft.
What do students like you say about this course?
Andrew says: "I enjoyed this course, and I learned some really useful things. The Calculation Group clarified this relatively new feature for me, so I will use it in the future. I'm taking my DP-600 exam soon. This course has filled in my knowledge of Fabric. I've even activated my Fabric 60 Day Trial because of this course, so I can actually go through the steps of creating items and manipulating data first-hand. The corse was presented in clear and logical manner."
Saurabh says: "This course is great. Phillip has explained the concepts in details and hands on activities, practice activities and in depth explanation of advanced DAX functions, SQL, PySpark and KQL makes this course stand out. I am going to attempt DP 600 in next four days. Thank you Phillip, I learned new things in each video. Keep bringing such great courses. I love your such in depth hands on courses."
Jerry says: "Hands down, this is one of the best courses for DP-600 available on Udemy. I’ve purchased several other courses, but none compare to this one. It’s clear, concise, and focused, with no unnecessary content. I’ve received my certification, thanks to this excellent course. Highly recommend!"
It comes in four parts:
Part 1 - Power BI knowledge you will have gained if you have already studied for the PL-300 exam,
Part 2 - additional Power BI knowledge (not part of the PL-300 exam),
Part 3 - Fabric lakehouses and data warehouses using SQL, and
Part 4 - eventhouses using KQL.
Part 1 of this course is for you if you have not studied for Microsoft's PL-300 exam. If you have, then please join me in Section 1, and then skip to Part 2 (Section 9). In Part 1, we'll look at:
Installing and creating a report in Power BI Desktop and uploading it to Power BI Service,
Creating calculated columns and measures using DAX, and
Other PL-300 exam topics needed for the DP-600 exam.
In Part 2 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 3 of this course, we'll query and manipulate data in Fabric lakehouses and data warehouses using SQL.
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 Data Warehouse and use the SQL Analytics Endpoint to manipulate the data in SQL. We'll learn the 6 principle clauses in the SQL Select statement: SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY.
In Part 4 of this course, we'll look at the Eventhouses and KQL:
We'll create an eventhouse, see sample KQL queries, and how you can convert SQL queries to KQL.
We'll select, filter and aggregate data using KQL.
We'll expand our KQL queries using string, number, datetime and timespan functions.
Finally, we'll transform data using KQL, merging and joining data, and identify and resolve duplicate and missing data.
No prior knowledge is assumed. We will start from the beginning for all languages and items, although any prior knowledge of DAX, SQL or KQL is useful.
Once you have completed the course, you will have a good knowledge of maintaining a data analytics solution, preparing data, and implementing and managing semantic models. And with some practice, you could even go for the official Microsoft certification DP-600 - wouldn't the "Microsoft Certified: Fabric Analytics Engineer Associate" certification 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?