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| Section | Weight | Objectives |
|---|---|---|
| Secure and monitor data solutions | 15-20% | - Monitor data solutions
|
| Design and manage the data model | 20-25% | - Implement and configure a data model
|
| Load and prepare data | 20-25% | - Ingest data from source systems
|
| Deploy and maintain a data solution | 10-15% | - Deploy data assets
|
| Clean, transform, and enrich data | 25-30% | - Enrich data
|
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NEW QUESTION # 91
You have a Fabric tenant.
You need to configure OneLake security for users shown in the following table.
The solution must follow the principle of least privilege.
Which permission should you assign to each user? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
You need to configure OneLake security for two users with the following requirements:
User1: Read all the Spark data
User2: Read all the SQL endpoint data
The available permissions are: Read, ReadAll, and ReadData.
Understanding the permissions:
Read # Grants access to metadata but not the data itself.
ReadData # Grants access to query data through SQL endpoints (SQL-based access).
ReadAll # Grants access to read data across all engines (including Spark and SQL endpoints).
Applying least privilege principle:
User1 (Spark access): Needs to read all the Spark data # Assign ReadAll because Spark requires this permission to access data in OneLake.
User2 (SQL endpoint access): Needs to read SQL endpoint data only # Assign ReadData, as this grants access to SQL endpoints without over-provisioning Spark access.
Final Answer:
User1: ReadAll
User2: ReadData
References:
Microsoft Fabric OneLake permissions
Fabric Lakehouse & SQL Endpoint security
NEW QUESTION # 92
You need to recommend which type of fabric capacity SKU meets the data analytics requirements for the Research division.
What should you recommend?
Answer: C
NEW QUESTION # 93
You have a Microsoft Power Bl semantic model.
You need to identify any surrogate key columns in the model that have the Summarize By property set to a value other than to None. The solution must minimize effort.
What should you use?
Answer: C
Explanation:
To identify surrogate key columns with the "Summarize By" property set to a value other than "None," the Best Practice Analyzer in Tabular Editor is the most efficient tool. The Best Practice Analyzer can analyze the entire model and provide a report on all columns that do not meet a specified best practice, such as having the
"Summarize By" property set correctly for surrogate key columns. Here's how you would proceed:
* Open your Power BI model in Tabular Editor.
* Go to the Advanced Scripting window.
* Write or use an existing script that checks the "Summarize By" property of each column.
* Execute the script to get a report on the surrogate key columns that do not have their "Summarize By" property set to "None".
* You can then review and adjust the properties of the columns directly within the Tabular Editor.
References: The functionality of the Best Practice Analyzer in Tabular Editor is documented in the community and learning resources for Power BI.
NEW QUESTION # 94
You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns.
You need to summarize order quantities by year and product. The solution must include the yearly sum of order quantities for all the products in each row.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Comprehensive Detailed Explanation
We need to write a query that summarizes order quantities by year and product, and also include the yearly total for all products in each row.
Step 1: What the query needs
Extract the year from SalesOrderDetail.ModifiedDate.
Join with the Product table to get the product name.
Aggregate with SUM(OrderQty).
Return grouped data by year and product, with an additional subtotal row per year (all products combined).
Step 2: Evaluate the SELECT Clause
We must extract the year using:
YEAR(so.ModifiedDate) AS OrderDate
This converts the ModifiedDate column into a year value for grouping.
Step 3: Evaluate the GROUP BY options
CUBE(YEAR, P.Name) # Produces all combinations of year totals, product totals, and grand totals. Too many combinations, not required.
GROUPING SETS # Could achieve the result but requires explicitly listing the sets. Less direct.
ROLLUP(YEAR, P.Name) # Produces grouping by (Year, Product) and then a subtotal per Year. Exactly what is required.
YEAR only # Would group only by year, losing per-product breakdown.
Correct: ROLLUP(YEAR(so.ModifiedDate), P.Name)
Step 4: Completed Query
SELECT
YEAR(so.ModifiedDate) AS OrderDate,
p.Name,
SUM(so.OrderQty) AS OrderQty
FROM dbo.SalesOrderDetail so
INNER JOIN dbo.Product p
ON p.ProductID = so.ProductID
GROUP BY ROLLUP(YEAR(so.ModifiedDate), p.Name);
Why This Works
YEAR(so.ModifiedDate) extracts year for grouping.
ROLLUP(YEAR, P.Name) provides both product-level totals and yearly subtotals.
Ensures the requirement: "include the yearly sum of order quantities for all the products in each row." References GROUP BY ROLLUP in T-SQL Aggregate functions in Microsoft Fabric warehouses
NEW QUESTION # 95
You have a Fabric tenant that contains a data warehouse.
You need to load rows into a large Type 2 slowly changing dimension (SCD). The solution must minimize resource usage.
Which T-SQL statement should you use?
Answer: B
Explanation:
Merg allow you to do :
- Insert new records for changes.
- Update existing records to mark them as historical.
- Maintain the history of changes efficiently.
NEW QUESTION # 96
......
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