The sale department requires reports that contain the number of sales transactions.
The COUNTROWS function counts the number of rows in the specified table, or in a table defined by an expression.
Reference:
https://docs.microsoft.com/en-us/dax/countrows-function-dax
Topic 1, Litware, Inc. Case Study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
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.

Explanation
Graphical user interface, text, application, email Description automatically generated

References: https://docs.microsoft.com/en-us/power-bi/refresh-scheduled-refresh

In Power BI Service the username and userprincipalname both return the email address, it's only in Power BI Desktop that username is domain/username rather than the email address. So I agree that userprincipalname is better generally as you always get the same value, the answer is correct and you can use username as your RLS since the role will be applied in the Service. See
https://community.powerbi.com/t5/Community-Blog/USERNAME-v-s-USERPRINCIPALNAME-in-RLS-for-P for more information.

Explanation
According to Microsoft Certified: Power BI Data Analyst Associate1, Power Query Editor is a tool that lets you connect to one or many data sources, shape and transform the data to meet your needs, then load that model into Power BI Desktop2.
One of the transformations you can perform in Power Query Editor is extract date from text, which creates a date value from a textual representation3. For example, given a text column like this:
Logged
2018-12-31 at 08:59
2019-01-01 at 09:15
You can extract the date part by using the Date.FromText function with a specific format4. The result will be:
Logged
Date
2018-12-31 at 08:59
2018-12-31
2019-01-01 at 09:15
2019-01-01
This makes it possible to use a built-in date hierarchy for analysis.

Scenario: The On-Time Shipping report will show the following metrics for a selected shipping month or quarter:
The percentage of orders that were shipped late by country and shipping region Customers that had multiple late shipments during the last quarter Note: Bar and column charts are some of the most widely used visualization charts in Power BI. They can be used for one or multiple categories. Both these chart types represent data with rectangular bars, where the size of the bar is proportional to the magnitude of data values.
The difference between the two is that if the rectangles are stacked horizontally, it is called a bar chart. If the rectangles are vertically aligned, it is called a column chart.
Reference:
https://www.pluralsight.com/guides/bar-and-column-charts-in-power-bi