Last weekend, I took the beta version of the DP600 exam. Today, the results were released, and I am happy to report that I passed. The DP600 exam is an associate-level certification. exam that tests the candidates in the areas below:
- Lakehouses
- Data warehouses
- Notebooks
- Dataflows
- Data pipelines
- Semantic models
- Reports
As I had noted in an earlier blogpost, that, Microsoft Fabric attempts to get everything under one roof and package it as a SAAS solution.
Anyway, the reason for this post is to outline some tips and tricks so that you can make the most of this exam, now that it is out of beta!
I would not reveal much details about the questions, to ensure I do not break the Microsoft no-disclosure agreement (NDA).
Exam format:
Skills measured
- Plan, implement, and manage a solution for data analytics (10–15%)
- Prepare and serve data (40–45%)
- Implement and manage semantic models (20–25%)
- Explore and analyze data (20–25%)
- Around 40-60 questions including one or more case studies, drag and drop, fill up the blanks, type in and multiple choice. Details regarding Microsoft exam format can be found here.
- Case studies will require complex decision-making.
- The exam expects you to have coding knowledge in SQL, DAX, PySpark, Scala, Power Query.
Preparation tips:
- Go ahead and schedule the exam first. Don't wait till you complete preparation. With a hard deadline in front of you, you will be bound to spend time learning. I have seen people who keep preparing and preparing and keep delaying their exams. It doesn't help. Microsoft allows you to reschedule exam too. I have done that in the past. So, don't worry.
- Ensure you have enough hands-on done while preparing.
- I completed all the MS learn modules related to the exam as part of instructor-led training as well as the self-paced ones. Absolutely essential to have a trial Fabric subscription.
- I went through the practice assessments multiple times. For questions where I failed to give the correct answer, I went through the reference materials to understand the concepts.
- Apart from the entire MS Learn path that one needs to complete, I went over the syllabus and did my own curation of links. Sharing them here. Some of the links may be repeated, so feel free to ignore repetitions.
- I found the exam cram sessions very helpful too!
- Don't look for dumps. First of all, it is against Microsoft policy, and second of all, even if you pass with dumps, you will gain no knowledge necessary to implement analytics solutions with Microsoft Fabric. That is the end goal, not just adding a fancy credential to our resume!
https://learn.microsoft.com/fabric/enterprise/licenses#microsoft-fabric-license-types
- Implement a lakehouse with Microsoft Fabric
- Create and manage Power BI assets using XMLA endpoint
- Publish to web in Microsoft Fabric
- Lakehouse sharing in Microsoft Fabric
- Scale capacity in Microsoft Fabric
- Manage premium service in Power BI
- Power BI projects overview
- Manage analytics development lifecycle
- Use XMLA endpoint to create and manage Power BI datasets
- Connect tools to Power BI premium service
- Data Wrangler in Microsoft Fabric
- Rankx function in DAX
- Explore data in a lakehouse
- Notebook visualization in Microsoft Fabric
- Power BI Desktop performance analyzer
- DAX query view in Power BI
- Waterfall charts in Power BI
- WHERE clause in Transact-SQL
- Ranking functions in Transact-SQL
- Joins in SQL Server
- LAG function in Transact-SQL
- Load data to a lakehouse in Microsoft Fabric
- OneLake shortcuts: https://learn.microsoft.com/fabric/onelake/onelake-shortcuts
- How do shortcuts handle deletions in OneLake: https://learn.microsoft.com/fabric/onelake/onelake-shortcuts#how-do-shortcuts-handle-deletions
- Lakehouse data preparation tutorial: https://learn.microsoft.com/fabric/data-engineering/tutorial-lakehouse-data-preparation
- Split columns by delimiter in Power Query: https://learn.microsoft.com/power-query/split-columns-delimiter
- Lakehouse partition tutorial: https://learn.microsoft.com/fabric/data-factory/tutorial-lakehouse-partition
- Considerations when choosing a data loading approach: https://learn.microsoft.com/fabric/data-engineering/load-data-lakehouse#considerations-when-choosing-approach-to-load-data
- Ingest data with Microsoft Fabric: https://learn.microsoft.com/training/paths/ingest-data-with-microsoft-fabric/
- Use Dataflow Gen 2 in Microsoft Fabric: https://learn.microsoft.com/training/modules/use-dataflow-gen-2-fabric/
- Data Factory pipeline runs: https://learn.microsoft.com/fabric/data-factory/pipeline-runs
- Use Data Factory pipelines in Microsoft Fabric: https://learn.microsoft.com/training/modules/use-data-factory-pipelines-fabric/
- Understand and optimize dataflow refresh in Power BI: https://learn.microsoft.com/power-bi/transform-model/dataflows/dataflows-understand-optimize-refresh
- Star schema for data modeling in Power BI: https://learn.microsoft.com/power-bi/guidance/star-schema
- Snowflake dimensions in star schema: https://learn.microsoft.com/power-bi/guidance/star-schema#snowflake-dimensions
- Load data to tables in Microsoft Fabric: https://learn.microsoft.com/fabric/data-engineering/load-to-tables
- Merge queries with left outer join in Power Query: https://learn.microsoft.com/power-query/merge-queries-left-outer
- Delta optimization and V-Order: https://learn.microsoft.com/fabric/data-engineering/delta-optimization-and-v-order?tabs=sparksql
- Configure high concurrency session notebooks: https://learn.microsoft.com/fabric/data-engineering/configure-high-concurrency-session-notebooks
- Lakehouse table maintenance: https://learn.microsoft.com/fabric/data-engineering/lakehouse-table-maintenance
- Best practices for developing complex dataflows in Power Query: https://learn.microsoft.com/power-query/dataflows/best-practices-developing-complex-dataflows
- Microsoft Fabric licensing: https://learn.microsoft.com/fabric/enterprise/licenses#microsoft-fabric-license-types
- Implement a lakehouse with Microsoft Fabric: https://learn.microsoft.com/training/paths/implement-lakehouse-microsoft-fabric/
- Sort columns in Power Query: https://learn.microsoft.com/power-query/sort-columns
- Working with duplicates in Power Query: https://learn.microsoft.com/power-query/working-with-duplicates
- Table constraints in Microsoft Fabric data warehouse: https://learn.microsoft.com/fabric/data-warehouse/table-constraints
- Merge queries overview in Power Query: https://learn.microsoft.com/power-query/merge-queries-overview
- Power Query folding: https://learn.microsoft.com/power-query/power-query-folding
- Storage modes in Power BI aggregations: https://learn.microsoft.com/power-bi/transform-model/aggregations-advanced#storage-modes
- Incremental refresh with XMLA in Power BI: https://learn.microsoft.com/power-bi/connect-data/incremental-refresh-xmla
- Detect whether queries hit or miss aggregations in Power BI: https://learn.microsoft.com/power-bi/transform-model/aggregations-advanced#detect-whether-queries-hit-or-miss-aggregations
- Notebook visualization in Microsoft Fabric: https://learn.microsoft.com/en-us/fabric/data-engineering/notebook-visualization
- Create relationships in a Power BI model
- Model relationships in Power BI Desktop
- Using composite models in Power BI Desktop
Exam tips:
- This is a time-bound exam. So effective time management is crucial. You do not want to end up not being able to answer all questions. Case studies are timed separately but still part of the overall time that the exam allows, so ensure you keep time for case studies. I submitted my exam one minute before the final bell.
- You need to get at least 700 out of 1000 to pass! And there is no negative marking, so attempt all you can!
- Don't spend too much time on a single question. If you are not sure, guess an answer and mark it for review later, so you can come back and have a re-look.
- The exam allows opening MS Learn, use it judiciously. If you search MS Learn for every question, you will run out of time without answering all. I suggest using MS Learn only for the questions that you marked for review!
- I took my exam from the Pearson exam center. I suggest the same. There will be an invigilator who will proctor the exam and you will need to show your pockets and leave all your belongings in the locker. I had two other guys sitting next to me giving their own exams (not DP600), but I did not face any disturbance or problems due to them. If you take the exam from a Pearson center then you are also insured in case there are infrastructure or network-related issues. If the same happens from your home, the voucher / your money could be wasted.
In conclusion, DP600 is a tough exam. Don't take it lightly - right from the way you prepare to giving your ultimate best during the exam. In terms of difficulty, I would place it somewhere between Azure Data Engineer Associate and Azure Solutions Architect Expert, which I have earned in the past. Study all you can. Practice all you can. Don't rely solely on one source of training/learning.
I wish you all the best. If any of the links do not work out, let me know in the comments and I'll correct them. Would love to know your experiences too, with this brand new exam!
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