Microsoft Fabric was introduced almost a year ago and the certification associated with it was released during Jan 2024. It was in beta for 2 months and now it is generally available to be taken up.
Now that the exam is available generally, let us see what you need to prepare and the things you must learn.
DP-600 is a comprehensive exam that has a wide range of topics that needs to be covered before taking the exam.
If this is the first time you are taking a Microsoft Exam, it is good to know the format of the exam to begin with.
The exam usually has 55-60 questions in the following format:
The number of questions is around 55-60 and it includes case study questions as well. The case studies are usually 1-2 in number, and they have multiple questions in relation to the case study.
Microsoft documentation will be available for use throughout the exam. But it is important that you balance the allotted time while using the documentation.
The complete skillset required for the exam is described here:
We have described below the skillsets required from a developer perspective. This makes it easier to understand what are the things that a developer must know.
DP-600 requires the candidates be familiar with SQL, Power Query and DAX at least at intermediate level. Python is also necessary, but this has more to do with PySpark functions.
With respect to the skillset, we have provided below the skillset that is asked in a simpler manner.
The content of the exam can be split into categories: Power BI, Fabric Data Engineering and Others
Within Power BI, we can further subdivide the topics that can be covered
Below are the links you can use to start learning from scratch the skillsets required for the exam. Further below, we have provided the links that are helpful for each section of the skillset described in study guide.
Video links that help you to know end to end:
Microsoft Fabric – DP 600 Certificate Training (youtube.com)
Documentation:
Microsoft Fabric documentation – Microsoft Fabric | Microsoft Learn
Get started with Microsoft Fabric – Training | Microsoft Learn
End-to-end tutorials in Microsoft Fabric – Microsoft Fabric | Microsoft Learn
Topic | Resource 1 | Resource 2 |
---|---|---|
Identify requirements for a solution, including components, features, performance, and capacity stock-keeping units(SKUs) | MSDoc | |
Recommend settings in the Fabric admin portal | MSDoc | Youtube |
Choose a data gateway type | MSDoc | Youtube |
Create a custom Power BI report theme | MSDoc | Youtube |
Topic | Resource 1 | Resource 2 | Resource 3 |
---|---|---|---|
Implement workspace and item-level access controls for Fabric items | MSDoc | MSDoc | |
Implement data sharing for workspaces, warehouses, and lakehouses | MSDoc | ||
Manage sensitivity labels in semantic models and lakehouses | MSDoc | ||
Configure Fabric-enabled workspace settings | MSDoc | Youtube | MSDoc |
Manage Fabric capacity | Blog | Blog |
Topic | Resource 1 | Resource 2 |
---|---|---|
Implement version control for a workspace | Youtube | MSDoc |
Create and manage a Power BI Desktop project(.pbip) | MSDoc | Blog |
Plan and implement deployment solutions | MSDoc | Youtube |
Perform impact analysis of downstream dependencies from lakehouses, data warehouses, dataflows, and semantic models | MSDoc | |
Deploy and manage semantic models by using the XMLA endpoint | MSDoc | |
Create and update reusable assets, including Power BI template(.pbit) files, Power BI data source(.pbids) files, and shared semantic models | Blog |
Topic | Resource 1 | Resource 2 | Resource 3 | Resource 4 |
---|---|---|---|---|
Ingest data by using a data pipeline, dataflow, or notebook | Blog | Youtube | MSDoc | MSDoc |
Create and manage shortcuts | Blog | MSDoc | ||
Implement file partitioning for analytics workloads in a lakehouse | MSDoc | |||
Create views, functions, and stored procedures | Blog | Blog | ||
Enrich data by adding new columns or tables | Blog | Blog |
Topic | Resource 1 | Resource 2 | Resource 3 |
---|---|---|---|
Choose an appropriate method for copying data from a Fabric data source to a lakehouse or warehouse | MSDoc | MSDoc | |
Copy data by using a data pipeline, dataflow, or notebook | MSDoc | ||
Add stored procedures, notebooks, and dataflows to a data pipeline | MSDoc | Blog | |
Schedule data pipelines | MSDoc | ||
Schedule dataflows and notebooks | MSDoc | MSDoc | Youtube |
Note: Some of the transformation skills are not specific to any tool and can be achieved using Spark, Dataflow or T-SQL. Links have been provided for each of them.
Topic | Resource 1 | Resource 2 | Resource 3 |
---|---|---|---|
Implement a data cleansing process | |||
Implement a star schema for a lakehouse or warehouse, including Type 1 and Type 2 slowly changing dimensions | MSDoc | MSDoc | |
Implement bridge tables for a lakehouse or a warehouse | MSDoc | ||
Denormalize data | Blog | Blog | |
Aggregate or de-aggregate data | MSDoc | Blog | Blog |
Merge or join data | Blog | MSDoc | Youtube |
Identify and resolve duplicate data, missing data, or null values | Blog | Blog | |
Convert data types by using SQL or PySpark | MSDoc | Blog | |
Filter data | Blog | MSDoc |
Topic | Resource 1 | Resource 2 |
---|---|---|
Identify and resolve data loading performance bottlenecks in dataflows, notebooks, and SQL queries | MSDoc | |
Implement performance improvements in dataflows, notebooks, and SQL queries | Blog | |
Identify and resolve issues with Delta table file sizes | Blog | MSDoc |
Topic | Resource 1 | Resource 2 | Resource 3 |
---|---|---|---|
Choose a storage mode, including Direct Lake | Blog | Blog | |
Identify use cases for DAX Studio and Tabular Editor 2 | Youtube | Blog | |
Implement a star schema for a semantic model | MSDoc | Blog | Blog |
Implement relationships, such as bridge tables and many-to-many relationships | MSDoc | Blog | |
Write calculations that use DAX variables and functions, such as iterators, table filtering, windowing, and information functions | MSDoc | MSDoc | |
Implement calculation groups, dynamic strings, and field parameters | Blog | Blog | |
Design and build large format dataset | Blog | MSDoc | |
Design and build composite models that include aggregations | Blog | MSDoc | |
Implement dynamic row-level security and object-level security | Blog | MSDoc | |
Validate row-level security and object-level security | MSDoc | Blog |
Topic | Resource 1 | Resource 2 | Resource 3 |
---|---|---|---|
Implement performance improvements in queries and report visuals | Blog | Blog | MSDoc |
Improve DAX performance by using DAX Studio | Blog | ||
Optimize a semantic model by using Tabular Editor 2 | Blog | Blog | |
Implement incremental refresh | Blog | MSDoc |
Note: Within this sub-topic, there exists these skillsets- implementing descriptive, diagnostic, prescriptive and predictive analytics. These skillsets are so vast that they cannot be covered using couple of links. We would suggest working with the various visuals available in Power BI and get an understanding of the different options available.
Design Power BI reports – Training.|Microsoft Learn
Perform advanced analytics in Power BI – Training.|.Microsoft Learn
Topic | Resource 1 | Resource 2 |
---|---|---|
Profile data | MSDoc | Youtube |
Topic | Resource 1 | Resource 2 |
---|---|---|
Query a lakehouse in Fabric by using SQL queries or the visual query editor | MSDoc | Blog |
Query a warehouse in Fabric by using SQL queries or the visual query editor | MSDoc | MSDoc |
Connect to and query datasets by using the XMLA endpoint | Blog | Blog |
We hope that this blog with the link aggregations will help you in preparing for the DP-600 exam and to become a certified Fabric Analytics Engineer. We wish you all the best from Data Crafters!
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