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Microsoft PL-300 Exam Syllabus Topics:

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

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Microsoft Power BI Data Analyst Sample Questions (Q238-Q243):

NEW QUESTION # 238
Hotspot Question
You use Power Query Editor to preview the data shown in the following exhibit.

You confirm that the data will always start on row 3, and row 3 will always contain the column names.
How should you shape the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 239
You need to create a visualization to meet the reporting requirements of the sales managers.
How should you create the visualization? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-kpi

NEW QUESTION # 240
You have a CSV file that contains user complaints. The file contains a column named Logged. Logged contains the date and time each compliant occurred. The data in Logged is in the following format: 2018-12-
31 at 08:59.
You need to be able to analyze the complaints by the logged date and use a built-in date hierarchy.
What should you do?

A. Apply a transform to extract the last 11 characters of the Logged column and set the data type of the new column to Date.
B. Apply a transform to extract the first 11 characters of the Logged column.
C. Create a column by example that starts with 2018-12-31 and set the data type of the new column to Date
.
D. Change the data type of the Logged column to Date.

Answer: C

NEW QUESTION # 241
Note: This question is a part of a series of questions that present the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You have a Microsoft SQL Server database that has the tables shown in the Database Diagram exhibit. (Click the Exhibit.)

You plan to develop a Power BI model as shown in the Power BI Model exhibit. (Click the Exhibit).

You plan to use Power BI to import data from 2013 to 2015.
Product Subcategory [Subcategory] contains NULL values.
End of repeated scenario.
You implement the Power BI model.
You need to add a measure to rank total sales by product. The results must appear as shown in the following table.

Which DAX formula should you use?

A. Product Ranking= RANKX (ALL, ('Product'), [SalesAmount], , DESC, Dense)
B. Product Ranking= RANKX (ALL ('Product'), [SalesAmount], , Asc, Dense
C. Product Ranking= RANKX (ALL, ('Product'), [SalesAmount], , DESC, Skip)
D. Product Ranking= RANKX (Product, [SalesAmount], , DESC, Skip)

Answer: A

Explanation:
References: https://msdn.microsoft.com/en-us/library/gg492185.aspx

NEW QUESTION # 242
Drag and Drop Question
You have two Microsoft Excel workbooks in a Microsoft OneDrive folder.
Each workbook contains a table named Sales. The tables have the same data structure in both workbooks.
You plan to use Power BI to combine both Sales tables into a single table and create visuals based on the data in the table. The solution must ensure that you can publish a separate report and dataset.
Which storage mode should you use for the report file and the dataset file? To answer, drag the appropriate modes to the correct files. Each mode 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:
Report file: Import: In Power BI, when you import data, it means that the data is loaded into the Power BI Desktop file. In this case, you would import the data from both Excel workbooks into your Power BI Desktop report file. This allows you to create visuals and reports based on the imported data. Importing the data ensures that you can work with the data even when you're not connected to OneDrive.
Dataset: DirectQuery: To keep the data in OneDrive and maintain a live connection to the source, you should use DirectQuery for the dataset. DirectQuery allows Power BI to retrieve and query data from the original data source (in this case, the Excel workbooks in OneDrive) in real-time without importing it into the dataset. This ensures that your dataset is always up-to-date and reflects changes made to the source data.

NEW QUESTION # 243
......

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