Practice online once, and the material goes with you everywhere. Prep4SureReview built its DP-600 package for real life: 212 practice questions accessible on computers and mobile phones, plus a printable PDF for offline consolidation wherever paper beats screens.
Microsoft DP-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prepare data for analytics | 45–50 | - Implement data storage structures
|
| Maintain a data analytics solution | 25–30 | - Implement security and governance
|
| Implement and manage semantic models | 25–30 | - Deploy and maintain semantic models
|
DP-600 Exam FAQ: Format, Prep, and Purchase
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The Microsoft Implementing Analytics Solutions Using Microsoft Fabric exam contains 40–60 to complete within 100 minutes. Knowing your pacing beforehand is exactly what the Prep4SureReview Desktop Test Engine's timed simulations are for.
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Three versions of the same study materials, provided because different customers have various needs: a printable, expert-prepared PDF in Q&A form with free demo download and instant access; a Desktop Test Engine for Windows that simulates the real exam with two practice modes and works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. The 212 practice questions are identical across versions — just choose the one you like. All include 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
The official Microsoft Implementing Analytics Solutions Using Microsoft Fabric outline defines 3 domains. The leading three are Prepare data for analytics (45–50), Maintain a data analytics solution (25–30), and Implement and manage semantic models (25–30). The full list is in the topics section above, and Prep4SureReview's 212 practice questions cover each one.
No mandatory prerequisites; recommended experience with data modeling, SQL, DAX, and Microsoft Fabric components Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
The DP-600 exam is a Microsoft certification exam validating the Microsoft Implementing Analytics Solutions Using Microsoft Fabric syllabus shown above. Candidates in 2026 prepare for it with Prep4SureReview's 212 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
The Microsoft Implementing Analytics Solutions Using Microsoft Fabric exam requires 700 / 1000 to pass, and registration costs USD 165. A failed attempt means paying the same fee again — a readiness check with the Prep4SureReview engines before booking is the cheaper option.
Microsoft recommends these training resources for the Microsoft Implementing Analytics Solutions Using Microsoft Fabric exam:
Follow the training with steady self-testing — the 212 practice questions from Prep4SureReview make that routine easy to maintain.
Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions:
You have a Microsoft Power Bl semantic model.
You plan to implement calculation groups.
You need to create a calculation item that will change the context from the selected date to month-to-date (MTD).
How should you complete the DAX expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
To create a calculation item that changes the context from the selected date to month-to-date (MTD), the appropriate DAX expression involves using the CALCULATE function to alter the filter context and the DATESMTD function to specify the month-to-date context.
The correct completion for the DAX expression would be:
In the first dropdown, select CALCULATE.
In the second dropdown, select SELECTEDMEASURE.
This would create a DAX expression in the form:
CALCULATE(
SELECTEDMEASURE(),
DATESMTD( ' Date ' [DateColumn])
)
You are analyzing customer purchases in a Fabric notebook by using PySpanc You have the following DataFrames:
You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling. You write the following code.
Which code should you run to populate the results DataFrame?
- A.
- B.
- C.
- D.
Correct Answer: B 🗳️
Explanation: Only visible for Prep4SureReview members. You can sign-up / login (it's free).
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData that stores the following data.
You need to create a column named FirstPickupDateTime that will contain the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
We have a KQL table (TaxiData) with columns:
VendorID
tpep_pickup_datetime (timestamp)
payment_type
total_amount
The requirement:
Create a new column FirstPickupDateTime
It should contain the first pickup timestamp per hour
Partitioning should be done by payment_type
Step 1: Which windowing function?
row_cumsum # running cumulative sum (not needed here).
row_rank_dense # assigns ranks without gaps, but does not guarantee minimum value only.
row_rank_min # gives the first/minimum value in each window partition. # Correct.
row_window_session # sessionization of events, not required.
So, the correct function is row_rank_min.
Step 2: Which comparison operator?
We need to select the row where the rank = 1 (the first per partition).
So the correct operator is == (equals).
Step 3: Partitioning
The KQL query should partition by:
bin(tpep_pickup_datetime, 1h) # buckets data into 1-hour windows
payment_type # partitions further by payment type
Completed KQL Query
TaxiData
| sort by tpep_pickup_datetime asc, payment_type asc
| extend FirstPickupDateTime = row_rank_min(tpep_pickup_datetime, 1h, 0m, payment_type)
| where FirstPickupDateTime == 1
This assigns a rank within each 1-hour, per-payment-type window, then keeps the first pickup timestamp.
Why This Works
row_rank_min # ensures we capture the first occurrence in each hour.
== # filters only the first row per partition.
bin(..., 1h) ensures grouping is by hour.
References
Kusto row_rank_min() function
KQL window functions
You need to recommend a solution to group the Research division workspaces.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
The requirement is to logically group the Research division workspaces and support filtering in the OneLake data hub.
Why Domain?
Microsoft Fabric allows you to assign workspace domains (e.g., Finance, HR, Research).
This provides a logical grouping of workspaces within the organization.
Domains are the only supported way to enable filtering in OneLake data hub by department.
Capacity or tenant grouping would not allow filtering by department in OneLake.
Why OneLake data hub?
The OneLake data hub is the centralized interface to browse and discover data assets across the organization.
With workspace domains configured, users can filter directly in the OneLake data hub by domain (e.g.,
"Research").
The Fabric Admin portal and Entra admin center are used for administration, not for workspace filtering in data discovery.
Correct Selection for the Hotspot
Grouping method: Domain
Tool: OneLake data hub
References
Workspace domains in Microsoft Fabric
Discover and filter data in OneLake data hub
Final Answer:
Grouping method = Domain
Tool = OneLake data hub
You have a Fabric workspace named Workspace1 that is assigned to a newly created Fabric capacity named Capacity1.
You create a semantic model named Model1 and deploy Model1 to Workspace1.
You need to publish changes to Model1 directly from Tabular Editor.
What should you do?
- A. For Workspace1, enable Git integration.
- B. For Capacity1, set XMLA Endpoint to Read Write.
- C. For Model1, enable external sharing.
- D. For Workspace1, create a managed private endpoint.
Correct Answer: B 🗳️
Explanation: Only visible for Prep4SureReview members. You can sign-up / login (it's free).
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