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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
  • 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.
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 (Q114-Q119):

NEW QUESTION # 114
You have a Fabric tenant that contains the workspaces shown in the following table.

You have a deployment pipeline named Pipeline1 that deploys items from Workspace_DEV to Workspace_TEST. In Pipeline1, all items that have matching names are paired.
You deploy the contents of Workspace_DEV to Workspace_TEST by using Pipeline1.
What will the contents of Workspace_TEST be once the deployment is complete?

Answer: C

Explanation:
Workspace_DEV contents:
Lakehouse1, Notebook1, Pipeline1, SemanticModel1
Workspace_TEST contents (before deployment):
Lakehouse2, Notebook2, SemanticModel1
After deployment:
SemanticModel1 # same name, so it will be paired and overwritten with the DEV version.
Lakehouse1 and Notebook1 # new items, so they will be added to TEST.
Lakehouse2 and Notebook2 # remain because they don't conflict in name.
Pipeline1 # new item, so it will also be added.
So the final content is:
Lakehouse1, Lakehouse2, Notebook1, Notebook2, Pipeline1, SemanticModel1 The answer: B Reference:
Deployment pipelines pairing behavior


NEW QUESTION # 115
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 # 116
You have a Fabric tenant that contains a lakehouse named Lakehouse1. You have forecast data stored in Azure Data Lake Storage Gen2. You plan to ingest the forecast data into Lakehouse1.
The data is already formatted, and you do NOT need to apply any further data transformations.
The solution must minimize development effort and costs.
Which method should you recommend to efficiently ingest the data?

Answer: D


NEW QUESTION # 117
You have a data warehouse that contains the following tables:

You have a T-SQL query named Query1 that contains the following statements.

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 118
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: D

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 # 119
......

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