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Microsoft PL-300 Exam Syllabus Topics:

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

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Microsoft Power BI Data Analyst Sample Questions (Q470-Q475):

NEW QUESTION # 470
You have two tables named Customers and Invoice in a Power BI model. The Customers table contains the following fields:
CustomerID
Customer City
Customer State
Customer Name
Customer Address 1
Customer Address 2
Customer Postal Code
The Invoice table contains the following fields:
Order ID
Invoice ID
Invoice Date
Customer ID
Total Amount
Total Item Count
The Customers table is related to the Invoice table through the Customer ID columns. A customer can have many invoices within one month.
The Power BI model must provide the following information:
The number of customers invoiced in each state last month
The average invoice amount per customer in each postal code
You need to define the relationship from the Customers table to the Invoice table. The solution must optimize query performance.
What should you configure? 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/transform-model/desktop-relationships-understand

NEW QUESTION # 471
You receive annual sales data that must be included in Power Bl reports.
From Power Query Editor, you connect to the Microsoft Excel source shown in the following exhibit.

You need to create a report that meets the following requirements:
* Visualizes the Sales value over a period of years and months
* Adds a slicer for the month
* Adds a slicer for the year

Answer:

Explanation:

Explanation

NEW QUESTION # 472
Case Study 1 - Litware, Inc.
Overview
Litware, Inc. is an online retailer that uses Microsoft Power Bl dashboards and reports. The company plans to leverage data from Microsoft SQL Server databases, Microsoft Excel files, text files, and several other data sources.
Litware uses Azure Active Directory (Azure AD) to authenticate users.
Existing Environment
Sales Data
Litware has online sales data that has the SQL schema shown in the following table.

In the Date table, the dateid column has a format of yyyymmdd and the month column has a format of yyyymm. The week column in the Date table and the weekid column in the Weekly_Returns table have a format of yyyyww. The regionid column can be managed by only one sales manager.
Data Concerns
You are concerned with the quality and completeness of the sales data. You plan to verify the sales data for negative sales amounts.
Reporting Requirements
Litware identifies the following technical requirements:
- Executives require a visual that shows sales by region.
- Regional managers require a visual to analyze weekly sales and
returns.
- Sales managers must be able to see the sales data of their respective region only.
- The sales managers require a visual to analyze sales performance
versus sales targets.
- The sale department requires reports that contain the number of sales transactions.
- Users must be able to see the month in reports as shown in the
following example: Feb 2020.
- The customer service department requires a visual that can be
filtered by both sales month and ship month independently.
- The maximum allowed latency to include transactions in reports is
five minutes.
You need to create relationships to meet the reporting requirements of the customer service department.
What should you create?

A. an additional date table named ShipDate, a one-to-many relationship from Sales[sales_date_id]to Date[date_id], and a one-to-many relationship from Sales[sales_ship_date_id]to ShipDate[date_id]
B. a one-to-many relationship from Date[date_id]to Sales[sales_date_id]and another one-to-many relationship from Date[date_id]to Weekly_Returns[week_id]
C. a one-to-many relationship from Date[date_id]to Sales[sales_date_id]and another one-to-many relationship from Date[date_id]to Sales[sales_ship_date_id]
D. a one-to-many relationship from Sales[sales_date_id]to Date[date_id]and a one-to- many relationship from Sales[sales_ship_date_id]to Date[date_id]
E. an additional date table named ShipDate, a many-to-many relationship from Sales[sales_date_id]to Date[date_id], and a many-to-many relationship from Sales[sales_ship_date_id]to ShipDate[date_id]

Answer: A

Explanation:
Scenario: The customer service department requires a visual that can be filtered by both sales month and ship month independently.
In Power BI Desktop, only one relationship can be active between a Fact table and Dimension table, so we need an extra table.
Use one-to-many relationship to be able to filter. Add a one-to-many relationship from both the Date tables to Sales table.
Reference:
https://docs.microsoft.com/en-us/power-bi/guidance/relationships-active-inactive
https://docs.microsoft.com/en-us/power-bi/transform-model/desktop-relationships-understand

NEW QUESTION # 473
You are creating a Microsoft Power Bl imported data model to perform basket analysis. The goal of the analysis is to identify which products are usually bought together in the same transaction across and within sales territories.
You import a fact table named Sales as shown in the exhibit. (Click the Exhibit tab.)

The related dimension tables are imported into the model.
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:

Reference:
https://finance-bi.com/power-bi-basket-analysis/

NEW QUESTION # 474
You are preparing a financial report in Power BI.
You connect to the data stored in a Microsoft Excel spreadsheet by using Power Query Editor as shown in the following exhibit.

You need to prepare the data to support the following:
* Visualizations that include all meas ures in the data over time
* Year-over-year calculations for all the measures
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:
1. Use first row as header
2. Unpivot all columns other than " Measure "
3. Rename " Attribute " to " Year "
4. Change data type of " Year " to date (Date > Year)

NEW QUESTION # 475
......

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