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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Prepare data: This section of the exam measures the skills of engineers and covers essential data preparation tasks. It includes establishing data connections and discovering sources through tools like the OneLake data hub and the real-time hub. Candidates must demonstrate knowledge of selecting the appropriate storage type—lakehouse, warehouse, or eventhouse—depending on the use case. It also includes implementing OneLake integrations with Eventhouse and semantic models. The transformation part involves creating views, stored procedures, and functions, as well as enriching, merging, denormalizing, and aggregating data. Engineers are also expected to handle data quality issues like duplicates, missing values, and nulls, along with converting data types and filtering. Furthermore, querying and analyzing data using tools like SQL, KQL, and the Visual Query Editor is tested in this domain.
Topic 2
  • Maintain a data analytics solution: This section of the exam measures the skills of administrators and covers tasks related to enforcing security and managing the Power BI environment. It involves setting up access controls at both workspace and item levels, ensuring appropriate permissions for users and groups. Row-level, column-level, object-level, and file-level access controls are also included, alongside the application of sensitivity labels to classify data securely. This section also tests the ability to endorse Power BI items for organizational use and oversee the complete development lifecycle of analytics assets by configuring version control, managing Power BI Desktop projects, setting up deployment pipelines, assessing downstream impacts from various data assets, and handling semantic model deployments using XMLA endpoint. Reusable asset management is also a part of this domain.
Topic 3
  • Implement and manage semantic models: This section of the exam measures the skills of architects and focuses on designing and optimizing semantic models to support enterprise-scale analytics. It evaluates understanding of storage modes and implementing star schemas and complex relationships, such as bridge tables and many-to-many joins. Architects must write DAX-based calculations using variables, iterators, and filtering techniques. The use of calculation groups, dynamic format strings, and field parameters is included. The section also includes configuring large semantic models and designing composite models. For optimization, candidates are expected to improve report visual and DAX performance, configure Direct Lake behaviors, and implement incremental refresh strategies effectively.

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q120-Q125):

NEW QUESTION # 120
You have a Fabric tenant that contains a lakehouse named LH1.
You create new tables in LH1.
You need to ensure that the tables are added automatically to the default semantic model.
What should you do?

Answer: A

Explanation:
To add objects such as tables or views to the default Power BI semantic model, you have options:
1. Manually enable the Sync the default Power BI semantic model setting that will automatically add objects to the semantic model. For more information, see Sync the default Power BI semantic model.
2. Manually add objects to the semantic model.
https://learn.microsoft.com/en-us/fabric/data-warehouse/default-power-bi-semantic-mode


NEW QUESTION # 121
You have a Fabric tenant that contains a lakehouse named LH1.
You need to deploy a new semantic model. The solution must meet the following requirements:
* Support complex calculated columns that include aggregate functions, calculated tables, and Multidimensional Expressions (MDX) user hierarchies.
* Minimize page rendering times.
How should you configure the model? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Supports complex calculated columns (with aggregate functions, calculated tables, MDX hierarchies).
Minimizes page rendering times.
Step 1 - Choosing the Mode
Direct Lake # Best for near real-time queries, avoids duplication, but has limitations (e.g., some complex calculated columns, MDX user hierarchies are not fully supported).
DirectQuery # Sends queries to the source each time. It supports complex expressions but is slow (not optimal for minimizing page rendering times).
Import # Data is loaded into VertiPaq in-memory engine, supports full DAX capabilities, calculated tables, MDX hierarchies, and provides fastest query performance.
# Correct choice: Import.
Step 2 - Choosing Query Caching
Capacity default # Relies on the workspace/capacity setting.
Off # Disables caching, which could slow down report rendering.
On # Ensures queries are cached for faster page rendering times.
# Correct choice: On.
Final Answer:
Mode: Import
Query Caching: On
References:
Semantic model storage modes in Fabric
Query caching in Power BI / Fabric


NEW QUESTION # 122
Hotspot Question
You have a Fabric tenant that contains a workspace named Workspace1 and a user named DBUser. Workspace1 contains a lakehouse named Lakehouse1. DBUser does NOT have access to the tenant.
You grant DBUser access to Lakehouse1 as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 123
You have a Fabric warehouse named Warehouse1 that contains a table named dbo.Product. dbo.Product contains the following columns.

You need to use a T-SQL query to add a column named PriceRange to dbo.Product. The column must categorize each product based on UnitPrice. The solution must meet the following requirements:
* If UnitPrice is 0, PriceRange is "Not for resale".
* If UnitPrice is less than 50, PriceRange is "Under $50".
* If UnitPrice is between 50 and 250, PriceRange is "Under $250".
* In all other instances, PriceRange is "$250+".
How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Comprehensive Detailed Explanation
We need to create a computed column PriceRange based on the UnitPrice column in the dbo.Product table.
Step 1: Requirements
If UnitPrice = 0 # "Not for resale"
If UnitPrice < 50 # "Under $50"
If UnitPrice >= 50 AND UnitPrice < 250 # "Under $250"
Otherwise # "$250+"
This matches a CASE expression in T-SQL.
Step 2: CASE Expression Structure
The syntax is:
CASE
WHEN condition THEN result
WHEN condition THEN result
ELSE result
END
Step 3: Apply to Problem
SELECT
Item,
UnitPrice,
PriceRange = CASE
WHEN UnitPrice = 0 THEN 'Not for resale'
WHEN UnitPrice < 50 THEN 'Under $50'
WHEN UnitPrice >= 50 AND UnitPrice < 250 THEN 'Under $250'
ELSE '$250+'
END
FROM [Warehouse1].[dbo].[Product];
Step 4: Why This is Correct
CASE starts the conditional evaluation.
ELSE handles the default branch ($250+).
END closes the expression.
Meets all requirements exactly.
References
CASE expression in T-SQL
Computed columns in T-SQL


NEW QUESTION # 124
You have a Fabric tenant that contains a lakehouse. You plan to use a visual query to merge two tables.
You need to ensure that the query returns all the rows that are present in both tables. Which type of join should you use?

Answer: A


NEW QUESTION # 125
......

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