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Microsoft PL-300 Exam Syllabus Topics:

Section	Weight	Objectives
Prepare the data	25-30%	- Get or connect to data 1. Configure data source settings, credentials, and privacy levels 2. Identify and connect to data sources or shared semantic models 3. Create and modify parameters 4. Choose storage modes: Import, DirectQuery, DirectLake - Load and configure data 1. Define table structures and properties 2. Integrate data from multiple sources 3. Configure data refresh settings - Profile and clean data 1. Evaluate data statistics and column properties 2. Resolve inconsistencies, null values, and errors 3. Transform data using Power Query Editor 4. Manage data types, columns, and rows
Model the data	25-30%	- Create model calculations 1. Use DAX: calculated columns, calculated tables, measures 2. Implement aggregation and time intelligence 3. Use CALCULATE and filter context - Optimize model performance 1. Optimize relationships and calculations 2. Use aggregations and composite models 3. Reduce cardinality and data size - Design data models 1. Create relationships: cardinality, cross-filter direction, security 2. Create common date tables 3. Implement role-playing dimensions 4. Define tables, columns, and hierarchies
Visualize and analyze data	25-30%	- Enhance reports with analytics 1. Create paginated reports 2. Apply conditional formatting and custom visuals 3. Use AI visuals, forecasts, and key influencers - Create reports and dashboards 1. Choose appropriate visualizations 2. Apply filters, slicers, and drill-through 3. Create dashboards and pinned elements 4. Design report layout, formatting, and interactivity - Perform data analysis 1. Create and manage bookmarks and tooltips 2. Interpret results and identify trends 3. Implement custom visuals and R/Python scripts
Manage and secure Power BI	15-20%	- Manage workspaces and assets 1. Create and configure workspaces 2. Manage data refresh and scheduled updates 3. Publish, update, and organize reports/datasets - Deploy and distribute content 1. Share reports, dashboards, and apps 2. Monitor usage and performance 3. Embed content in applications or websites - Implement security and governance 1. Manage permissions and access 2. Configure row-level security (RLS) and object-level security 3. Apply data sensitivity labels and protection

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Microsoft Power BI Data Analyst Sample Questions (Q131-Q136):

NEW QUESTION # 131
You have a Power Bl report for the marketing department.
The report reports on web traffic to a blog and contains data from the following tables.

There is a one-to-many relationship from Posts to Traffic that uses the URL and URL Visited columns.
The report contains the visuals shown in the following table.

The dataset takes a long time to refresh.
You need to modify Posts and Traffic queries to reduce toad times.
Which two actions will reduce the toad times? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Remove the rows in Traffic in which Traffic [URL visited] does not contain "blog''
B. Remove the rows in Posts m which Post [Publish Date] is in the last seven days.
C. Remove Posts [Full Text] and Posts [Summary].
D. Remove the rows m Traffic in which Traffic [Referring URL] does not start with "/"
E. Remove Traffic [IP Address], Traffic (Browser Agent], and Traffic [Referring URL).

Answer: A,C

Explanation:
All 4 visualizations are about blogs: so we can remove rows what do not contain "blog". We do not need columns Posts[Full Text] and Posts[Summary] in any visualization, they can be removed.

NEW QUESTION # 132
In Power BI Desktop, you are building a sales report that contains two tables. Both tables have row-level security (RLS) configured.
You need to create a relationship between the tables. The solution must ensure that bidirectional cross-filtering honors the RLS settings.
What should you do?

A. Create an inactive relationship between the tables and select Apply security filter in both directions.
B. Create an active relationship between the tables and select Apply security filter in both directions.
C. Create an inactive relationship between the tables and select Assume referential integrity.
D. Create an active relationship between the tables and select Assume referential integrity.

Answer: B

Explanation:
By default, row-level security filtering uses single-directional filters, whether the relationships are set to single direction or bi-directional. You can manually enable bi-directional cross-filtering with row-level security by selecting the relationship and checking the Apply security filter in both directions checkbox. Select this option when you've also implemented dynamic row-level security at the server level, where row-level security is based on username or login ID.

Reference:
https://docs.microsoft.com/en-us/power-bi/admin/service-admin-rls

NEW QUESTION # 133
You have a Power Bl query named Sates that imports the columns shown in the following table.

Usees only use the dale part of the Sales.Date field. Only rows with a Status of Finished are used in analysis.
You need to reduce the load times of the query without affecting the analysis.
Which two actions achieve this goal? Each correct answer presents a complete solution.
NOTL Each correct selection is worth one pant.

A. Change the data type of sale [Delivery_Time] to Integer
B. Remove the rows in which sales [status] has a value of Canceled.
C. Removes (Canceled Date).
D. Remove sales [Sales_Date].
E. Split Sales [Sale_Date] into separate date and time columns.

Answer: B,E

NEW QUESTION # 134
You have the tables shown in the following table.

The Impressions table contains approximately 30 million records per month.
You need to create an ad analytics system to meet the following requirements:
* Present ad impression counts for the day, campaign, and Site_name. The analytics for the last year are required.
* Minimize the data model size.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Group the impressions by Ad_id, Site_name, and Impression_date.Aggregate by using the CountRows function.
B. Create a calculated measure that aggregates by using the COUNTROWS function.
C. Create a calculated table that contains Ad_id, Site_name, and Impression_date.
D. Create one-to-many relationships between the tables.

Answer: B,D

Explanation:
Grouping in power query reduces the number of rows in the impression table that is gonna be loaded in the model. Creating relationships doesn't increase the size of the model.

NEW QUESTION # 135
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
From Power Query Editor, you profile the data shown in the following exhibit.

The IoT GUID and IoT ID columns are unique to each row in query.
You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.
Solution: You remove the loT GUID column and retain the loT ID column.
Does this meet the goal?

A. Yes
B. No

Answer: A

NEW QUESTION # 136
......

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