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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Implementing Analytics Solutions Using Microsoft Fabric |
| Exam Number: | DP-600 |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Certified: Fabric Analytics Engineer Associate |
| Available Languages: | Chinese (Simplified), Korean, Japanese, English |
| Certificate Validity Period: | 1 year |
| Passing Score: | 700/1000 |
| Exam Price: | $165 USD |
| Exam Format: | Drag-and-drop, Multiple-choice, Case studies |
| Sample Questions: | Microsoft DP-600 Sample Questions |
| Exam Way: | Online proctored or in-person testing center |
| Pre Condition: | Candidates should have foundational knowledge of data concepts, experience with Microsoft Fabric, and proficiency in data transformation and modeling. Familiarity with Power BI is recommended but not required. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/dp-600 |
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NEW QUESTION # 50
You have a Fabric warehouse that contains the following data.
The data has the following characteristics:
* Each customer is assigned a unique CustomerlD value.
* Each customer is associated to a single SalesRegion value.
* Each customer is associated to a single CustomerAddress value.
* The Customer table contains 5 million rows.
* All foreign key values are non-null.
You need to create a view to denormalize the data into a customer dimension that contains one row per distinct CustomerlD value. The solution must minimize query processing time and resources.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation:
The goal is to denormalize the data into a customer dimension with one row per distinct CustomerID, minimizing query processing time and resources. Since each customer is associated with a single SalesRegion and a single CustomerAddress, and all foreign key values are non-null, a left outer join is appropriate to ensure all customers from the Customer table are included, even if there are any unexpected missing addresses (though the problem states each customer has a single address). However, given the non-null foreign key constraint, an inner join could also work, but left outer join is safer and aligns with denormalization to ensure completeness.
The join condition should link the Customer table (C) with the CustomerAddress table (CA) using CustomerID, as this ensures each customer ' s address data is included.
The join with SalesRegion (SR) on SalesRegionID is already included in the query, and since each customer has a single SalesRegion, it fits the denormalization requirement.
The where CA.AddressType = ' Main Office ' filter ensures only the main office address is included, which is a valid constraint for a customer dimension.
Thus, the completed T-SQL statement would effectively denormalize the data while minimizing resource use by leveraging the existing relationships and constraints.
NEW QUESTION # 51
Drag and Drop Question
You have Fabric tenant that contains four workspaces named Development, Test, QA, and Production. All the workspaces are in Premium Per User (PPU) license mode.
You plan to use a release pipeline to support the development lifecycle from Development to Production.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
NEW QUESTION # 52
You need to refresh the Orders table of the Online Sales department. The solution must meet the semantic model requirements. What should you include in the solution?
Answer: C
Explanation:
Requirement: "The number of rows added to the Orders table during refreshes must be minimized." The Orders table has a sequential OrderID .
To minimize refresh size, you must only import new rows , not the entire table.
This requires retrieving the maximum OrderID currently loaded, then only loading rows with a greater OrderID.
So, the correct solution is to use a pipeline (ADF) with a dataflow to retrieve the maximum OrderID .
answer: C. an Azure Data Factory pipeline that executes a dataflow to retrieve the maximum value of the OrderID column in the destination lakehouse
NEW QUESTION # 53
Case Study 1 - Contoso
Overview
Contoso, Ltd. is a US-based health supplements company. Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.
Existing Environment
Identity Environment
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroup1 and ResearchReviewersGroup2.
Data Environment
Contoso has the following data environment:
- The Sales division uses a Microsoft Power BI Premium capacity.
- The semantic model of the Online Sales department includes a fact table named Orders that uses Import made. In the system of origin, the OrderID value represents the sequence in which orders are created.
- The Research department uses an on-premises, third-party data warehousing product.
- Fabric is enabled for contoso.com.
- An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Productline1. - The data is in the delta format.
- A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.
Requirements
Planned Changes
Contoso plans to make the following changes:
- Enable support for Fabric in the Power BI Premium capacity used by the Sales division.
- Make all the data for the Sales division and the Research division available in Fabric.
- For the Research division, create two Fabric workspaces named Productline1ws and Productine2ws.
- In Productline1ws, create a lakehouse named Lakehouse1.
- In Lakehouse1, create a shortcut to storage1 named ResearchProduct.
Data Analytics Requirements
Contoso identifies the following data analytics requirements:
- All the workspaces for the Sales division and the Research division must support all Fabric experiences.
- The Research division workspaces must use a dedicated, on-demand capacity that has per- minute billing.
- The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.
- For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
- For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.
- All the semantic models and reports for the Research division must use version control that supports branching.
Data Preparation Requirements
Contoso identifies the following data preparation requirements:
- The Research division data for Productline1 must be retrieved from Lakehouse1 by using Fabric notebooks.
- All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.
Semantic Model Requirements
Contoso identifies the following requirements for implementing and managing semantic models:
- The number of rows added to the Orders table during refreshes must be minimized.
- The semantic models in the Research division workspaces must use Direct Lake mode.
General Requirements
Contoso identifies the following high-level requirements that must be considered for all solutions:
- Follow the principle of least privilege when applicable.
- Minimize implementation and maintenance effort when possible.
Hotspot Question
You need to migrate the Research division data for Productline1. The solution must meet the data preparation requirements.
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:
Requirements: Use managed tables.
If you use saveAsTable() you don't need to specify the path "Table/"
If you you save() you specify the full path
NEW QUESTION # 54
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 # 55
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