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[Hardware] DP-600 exam collection guarantee DP-600 Implementing Analytics Solutions Using M

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【Hardware】 DP-600 exam collection guarantee DP-600 Implementing Analytics Solutions Using M

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Microsoft DP-600 Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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 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 (Q47-Q52):NEW QUESTION # 47
You have a data warehouse that contains a table named Stage. Customers. Stage-Customers contains all the customer record updates from a customer relationship management (CRM) system. There can be multiple updates per customer You need to write a T-SQL query that will return the customer ID, name, postal code, and the last updated time of the most recent row for each customer ID.
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:

* In the ROW_NUMBER() function, choose OVER (PARTITION BY CustomerID ORDER BY LastUpdated DESC).
* In the WHERE clause, choose WHERE X = 1.
To select the most recent row for each customer ID, you use the ROW_NUMBER() window function partitioned by CustomerID and ordered by LastUpdated in descending order. This will assign a row number of 1 to the most recent update for each customer. By selecting rows where the row number (X) is 1, you get the latest update per customer.
References =
* Use the OVER clause to aggregate data per partition
* Use window functions

NEW QUESTION # 48
Your company has a finance department.
You have a Fabric tenant, an Azure Storage account named storage1, and a Microsoft Entra group named Group1. Group1 contains the users in the finance department.
You need to create a new workspace named Workspace1 in the tenant. The solution must meet the following requirements:
- Ensure that the finance department users can create and edit items in Workspace1.
- Ensure that Workspace1 can securely access storage1 to read and write data.
- Ensure that you are the only admin of Workspace1.
- Minimize administrative effort.
You create Workspace1.
Which two actions should you perform next? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
  • A. Assign the Admin role to yourself.
  • B. Create a workspace identity.
  • C. Assign the Contributor role to each finance department user.
  • D. Assign the Contributor role to Group1.
Answer: B,D

NEW QUESTION # 49
You have a Fabric workspace named Workspace1 that contains a data flow named Dataflow1. Dataflow1 contains a query that returns the data shown in the following exhibit.

You need to transform the date columns into attribute-value pairs, where columns become rows.
You select the VendorlD column.
Which transformation should you select from the context menu of the VendorlD column?
  • A. Unpivot other columns
  • B. Remove other columns
  • C. Unpivot columns
  • D. Split column
  • E. Group by
Answer: C
Explanation:
The transformation you should select from the context menu of the VendorID column to transform the date columns into attribute-value pairs, where columns become rows, is Unpivot columns (B). This transformation will turn the selected columns into rows with two new columns, one for the attribute (the original column names) and one for the value (the data from the cells). References = Techniques for unpivoting columns are covered in the Power Query documentation, which explains how to use the transformation in data modeling.

NEW QUESTION # 50
You have a Fabric tenant that contains a warehouse named Warehouse!. Warehousel contains two schemas name schemal and schema2 and a table named schemal.city.
You need to make a copy of schemal.city in schema2. The solution must minimize the copying of data.
Which T-SQL statement should you run?
  • A. SELECT * INTO schema2.eity FROM schemal.city;
  • B. CREATE TABLE schema2.city AS SELECT * FROM schemal.city;
  • C. CREATE TABLE schema2.city AS CLONE OF schemal.city;
  • D. INSERT INTO schema2.city SELECT * FROM schemal.city;
Answer: C
Explanation:
INSERT INTO ... SELECT and SELECT INTO both physically copy all rows, which is heavy and not minimal.
CREATE TABLE AS SELECT (CTAS) also copies the data.
CREATE TABLE ... AS CLONE OF creates a shallow clone in Fabric Warehouse, meaning it references the existing data without duplicating it, minimizing storage and copying.
Correct answer: B.
Reference: Clone tables in Fabric warehouse

NEW QUESTION # 51
You have a Fabric tenant that contains a data pipeline.
You need to ensure that the pipeline runs every four hours on Mondays and Fridays.
To what should you set Repeat for the schedule?
  • A. Hourly
  • B. Daily
  • C. Weekly
  • D. By the minute
Answer: C
Explanation:
You should set Repeat for the schedule to Weekly (C). This allows you to specify the pipeline to run on specific days of the week, in this case, every four hours on Mondays and Fridays. References = Scheduling options for data pipelines are available in the Azure Data Factory documentation, which includes details on configuring recurring triggers.

NEW QUESTION # 52
......
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