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| Topic | Details |
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| 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.
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| Topic 2 | - 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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| Topic 3 | - 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.
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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q69-Q74):
NEW QUESTION # 69
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1.
You are creating a new data pipeline.
You plan to copy external data to Table1. The schema of the external data changes regularly.
You need the copy operation to meet the following requirements:
* Replace Table1 with the schema of the external data.
* Replace all the data in Table1 with the rows in the external data.
You add a Copy data activity to the pipeline. What should you do for the Copy data activity?
- A. From the Source tab, select Recursively
- B. From the Settings tab, select Enable staging
- C. From the Source tab, add additional columns.
- D. From the Destination tab, set Table action to Overwrite.
- E. From the Source tab, select Enable partition discovery
Answer: D
Explanation:
For the Copy data activity, from the Destination tab, setting Table action to Overwrite (B) will ensure that Table1 is replaced with the schema and rows of the external data, meeting the requirements of replacing both the schema and data of the destination table. References = Information about Copy data activity and table actions in Azure Data Factory, which can be applied to data pipelines in Fabric, is available in the Azure Data Factory documentation.
NEW QUESTION # 70
You have a Fabric tenant that contains a workspace named Workspace"!. You plan to deploy a semantic model named Model 1 by using the XMLA endpoint.
You need to optimize the deployment of Model!. The solution must minimize how long it takes to deploy Modell. What should you do in Workspace1?
- A. Select Large semantic model storage format
- B. Select Small semantic model storage format.
- C. Set Enable Cache for Shortcuts to On.
- D. Select Users can edit data models in the Power Bl service.
Answer: A
NEW QUESTION # 71
You have a Fabric lakehouse named Lakehouse1 that contains the following data.

You need build a T-SQL statement that will return the total sales amount by OrderDate only for the days that are holidays in Australia. The total sales amount must sum the quantity multiplied by the price on each row in the dbo.sales table.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

Step 1: Requirement
We need to calculate total sales amount by OrderDate.
Total Sales Amount = Quantity × UnitPrice per row.
Then SUM over all rows per OrderDate.
Only include rows where the OrderDate matches a public holiday in Australia.
Step 2: Calculation Logic
If we select s.Quantity * s.UnitPrice, it only computes row-level values.
To calculate the total sales amount per OrderDate, we need:
SUM(s.Quantity * s.UnitPrice) AS TotalSalesAmt
Thus, the correct calculation: SUM(s.Quantity * s.UnitPrice)
Step 3: Join Type
We want to return only those sales that occurred on public holidays in Australia.
If we used a LEFT JOIN, we'd include all sales regardless of holiday.
A FULL OUTER JOIN would include non-matching rows, not required.
A CROSS JOIN would duplicate results unnecessarily.
A RIGHT OUTER JOIN would include holidays with no sales, which is not needed.
The correct choice is an INNER JOIN on matching dates.
Step 4: Final Query
SELECT
s.OrderDate,
SUM(s.Quantity * s.UnitPrice) AS TotalSalesAmt
FROM dbo.sales AS s
INNER JOIN dbo.publicholidays AS ph
ON s.OrderDate = ph.Date
WHERE ph.countryOrRegion = ' Australia '
GROUP BY s.OrderDate;
Why This is Correct
SUM(s.Quantity * s.UnitPrice) # ensures sales are aggregated correctly.
INNER JOIN # ensures only rows where OrderDate matches a holiday are included.
WHERE ph.countryOrRegion = ' Australia ' # filters holidays to Australia only.
References
SUM (Transact-SQL)
JOIN operations in T-SQL
NEW QUESTION # 72
Hotspot Question
You have two Microsoft Power BI queries named Employee and Retired Roles.
You need to merge the Employee query with the Retired Roles query. The solution must ensure that duplicate rows in each query are removed.
Which column and Join Kind should you use in Power Query Editor? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point.

Answer:
Explanation:

NEW QUESTION # 73
You have a Fabric warehouse that contains a table named Sales.Orders. Sales.Orders contains the following columns.

You need to write a T-SQL query that will return the following columns.

How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

For the PeriodDate that returns the first day of the month for OrderDate, you should use DATEFROMPARTS as it allows you to construct a date from its individual components (year, month, day).
For the DayName that returns the name of the day for OrderDate, you should use DATENAME with the weekday date part to get the full name of the weekday.
The complete SQL query should look like this:
SELECT OrderID, CustomerID,
DATEFROMPARTS(YEAR(OrderDate), MONTH(OrderDate), 1) AS PeriodDate,
DATENAME(weekday, OrderDate) AS DayName
FROM Sales.Orders
Select DATEFROMPARTS for the PeriodDate and weekday for the DayName in the answer area.
NEW QUESTION # 74
......
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