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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Implementing Analytics Solutions Using Microsoft Fabric |
| Exam Number: | DP-600 |
| Exam Duration: | 120 minutes |
| Passing Score: | 700/1000 |
| Exam Price: | $165 USD |
| Certificate Validity Period: | 1 year |
| Related Certifications: | Microsoft Certified: Fabric Analytics Engineer Associate |
| Exam Format: | Case studies, Drag-and-drop, Multiple-choice |
| Real Exam Qty: | 40-60 |
| Available Languages: | Japanese, English, Korean, Chinese (Simplified) |
| 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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| Topic | Details |
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| Topic 1 |
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| Topic 2 |
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| Topic 3 |
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NEW QUESTION # 31
You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named I.H1 and a warehouse named DW1. I.H1 contains a table named signindata that is in the dho schema.
You need to create a stored procedure in DW1 that deduplicates the data in the signindata table.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Fach correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 32
You have a Fabric workspace named Workspace1 that contains a lakehouse named LH1. LH1 contains a folder named /Files/RegionA/ that stores raw CSV files.
You need to ensure that a group of analysts can access only the files in RegionA. The solution must follow the principle of least privilege.
Which two access controls should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
NEW QUESTION # 33
You have a semantic model named Model1 that contains data that relates to customers and their bank account balances.
Model1 has the following tables and columns.
A customer can have one or more accounts. Each account can be associated to multiple customers.
You need to ensure that users can query Model1 to identify the total transaction amounts by customer.
What should you add to Model1?
Answer: A
Explanation:
We need to define a many-to-many relation between DimAccount and DimCustomer. This can be done using a bridge table.
Note: Relate many-to-many dimensions
The classic many-to-many scenario relates two entities, for example bank customers and bank accounts. Consider that customers can have multiple accounts, and accounts can have multiple customers. When an account has multiple customers, they're commonly called joint account holders.
Modeling these entities is straight forward. One dimension table stores accounts, and another dimension table stores customers. As is characteristic of dimension tables, there's a unique identifier (ID) column in each table. To model the relationship between the two tables, a third table is required. This table is commonly referred to as a bridging table. In this example, it's purpose is to store one row for each customer-account association.
Reference:
https://learn.microsoft.com/en-us/power-bi/guidance/relationships-many-to-many
NEW QUESTION # 34
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: C
Explanation:
When you need to return all rows that are present in both tables, you use a full outer join. This type of join combines the results of both left and right outer joins and returns all rows from both tables, with matching rows from both sides where available. If there is no match, the result is NULL on the side of the join where there is no match.
Topic 1, Contoso, ltd.
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.
Identity Environment
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroupi and ReseachReviewefsGfoup2.
Data Environment
Contoso has the following data environment
* The Sales division uses a Microsoft Power B1 Premium capacity.
* The semantic model of the Online Sales department includes a fact table named Orders that uses import mode. In the system of origin, the OrderlD 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 Producthne1. 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.
Planned Changes
Contoso plans to make the following changes:
* Enable support for Fabric in the Power Bl 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 Producttmelws and Productline2ws.
* in Productlinelws. create a lakehouse named LakehouseV
* 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 ResearchRevtewersGroupl 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 Producthne2 must be retrieved from Lakehouset 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.
NEW QUESTION # 35
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 # 36
......
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