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Worksheets300-T2-26-63
Total questions: 37
Worksheet time: 37mins
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.
Create one-to-many relationships between the tables.
Group the Impressions query in Power Query by Ad_id, Site_name, and Impression_date. Aggregate by using the CountRows function.
Create a calculated table that contains Ad_id, Site_name, and Impression_date.
Create a calculated measure that aggregates by using the COUNTROWS function.
You are creating a Microsoft Power BI data model that has the tables shown in the following table.The Products table is related to the ProductCategory table through the ProductCategoryID column. Each product has one product category.You need to ensure that you can analyze sales by product category.How should you configure the relationship from ProductCategory to Products? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
Cardinality: One-to-many
Cross-filter direction: Single
Cardinality: One-to-one
Cross-filter direction: Single
Cardinality: One-to-one
Cross-filter direction: Both
Cardinality: One-to-many
Cross-filter direction: Both
You import a Power BI dataset that contains the following tables:✑ Date✑ Product✑ Product InventoryThe Product Inventory table contains 25 million rows. A sample of the data is shown in the following table.The Product Inventory table relates to the Date table by using the DateKey column. The Product Inventory table relates to the Product table by using theProductKey column.You need to reduce the size of the data model without losing information.What should you do?
Change Summarization for DateKey to Don't Summarize.
Remove the relationship between Date and Product Inventory
Change the data type of UnitCost to Integer.
Remove MovementDate.
You are enhancing a Power BI model that has DAX calculations.You need to create a measure that returns the year-to-date total sales from the same date of the previous calendar year.Which DAX functions should you use? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
Sales PYTD =
VAR startyear =
STARTOFYEAR (PREVIOUSYEAR ( 'Calendar'[Date]) )
VAR enddate =
LASTDATE( Sales[Date]) - 365
RETURN
CALCULATE( SUM (Sales[Sales]), SAMEPERIODLASTYEAR('Calendar'[Date],startyear, enddate))
Sales PYTD =
VAR startyear =
STARTOFYEAR (PREVIOUSYEAR ( 'Calendar'[Date]) )
VAR enddate =
LASTDATE( Sales[Date]) - 365
RETURN
CALCULATE( SUM (Sales[Sales]), DATESBETWEEEN('Calendar'[Date],startyear, enddate))
Sales PYTD =
VAR startyear =
STARTOFYEAR (PREVIOUSYEAR ( 'Calendar'[Date]) )
VAR enddate =
LASTDATE( Sales[Date]) - 365
RETURN
SUM( CALCULATE (Sales[Sales]), DATESBETWEEEN('Calendar'[Date],startyear, enddate))
Sales PYTD =
VAR startyear =
STARTOFYEAR (PREVIOUSYEAR ( 'Calendar'[Date]) )
VAR enddate =
LASTDATE( Sales[Date]) - 365
RETURN
SUM( CALCULATE (Sales[Sales]), SAMEPERIODLASTYEAR('Calendar'[Date],startyear, enddate))
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.
You are modeling data by using Microsoft Power BI. Part of the data model is a large Microsoft SQL Server table named Order that has more than 100 million records. During the development process, you need to import a sample of the data from the Order table. Solution: You add a report-level filter that filters based on the order date. Does this meet the goal?
Yes
No
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.
You have a Power BI report that imports a date table and a sales table from an Azure SQL database data source.
The sales table has the following date foreign keys:
✑ Due Date
✑ Order Date
✑ Delivery Date
You need to support the analysis of sales over time based on all the date foreign keys.
Solution: For each date foreign key, you add inactive relationships between the sales table and the date table. Does this meet the goal?
Yes
No
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.
You have a Power BI report that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys: ✑ Due Date ✑ Order Date ✑ Delivery Date You need to support the analysis of sales over time based on all the date foreign keys. Solution: From the Fields pane, you rename the date table as Due Date. You use a DAX expression to create Order Date and Delivery Date as calculated tables. Does this meet the goal?
Yes
No
You receive revenue data that must be included in Microsoft Power BI reports.You preview the data from a Microsoft Excel source in Power Query as shown in the following exhibit.You plan to create several visuals from the data, including a visual that shows revenue split by year and product.You need to transform the data to ensure that you can build the visuals. The solution must ensure that the columns are named appropriately for the data that they contain.Which three 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.
Select Department and Product and Unpivot Other Columns
Rename Attribute column to Year and the Value column to Revenue
Select Use First Row as Headers
Select Use First Row as Headers
Select Department and Product and Unpivot Other Columns
Rename Attribute column to Year and the Value column to Revenue
Select Department and Product and Unpivot Other Columns
Rename Attribute column to Revenue and the Value column to Year
Select Use First Row as Headers
Select Department and Product and Unpivot Other Columns
Rename Attribute column to Revenue and the Value column to Year
Select Use Header as First Row
You have a Power BI report named Orders that supports the following analysis:✑ Total sales over time✑ The count of orders over time✑ New and repeat customer countsThe data model size is nearing the limit for a dataset in shared capacity.The model view for the dataset is shown in the following exhibit.The data view for the Orders table is shown in the following exhibit.The Orders table relates to the Customers table by using the CustomerID column.The Orders table relates to the Date table by using the OrderDate columnSelect the correct statements.NOTE: Each correct selection is worth one point.
Summarizing Orders by the CustomerID, OrderID, and OrderDate columns will reduce model size while still supporting the current analysis. [Yes]
Removing the CustomerID column from Oders will reduce the model size while still supporting the current analysis. [Yes]
Removing the UnitPrice and Discount columns from Oders will reduce the model size while still supporting the current analysis. [Yes]
Summarizing Orders by the CustomerID, OrderID, and OrderDate columns will reduce model size while still supporting the current analysis. [Yes]
Removing the CustomerID column from Oders will reduce the model size while still supporting the current analysis. [No]
Removing the UnitPrice and Discount columns from Oders will reduce the model size while still supporting the current analysis. [Yes]
Summarizing Orders by the CustomerID, OrderID, and OrderDate columns will reduce model size while still supporting the current analysis. [Yes]
Removing the CustomerID column from Oders will reduce the model size while still supporting the current analysis. [No]
Removing the UnitPrice and Discount columns from Oders will reduce the model size while still supporting the current analysis. [No]
Summarizing Orders by the CustomerID, OrderID, and OrderDate columns will reduce model size while still supporting the current analysis. [No]
Removing the CustomerID column from Oders will reduce the model size while still supporting the current analysis. [No]
Removing the UnitPrice and Discount columns from Oders will reduce the model size while still supporting the current analysis. [Yes]
You are building a financial report by using Power BI.You have a table named financials that contains a column named Date and a column named Sales.You need to create a measure that calculates the relative change in sales as compared to the previous quarter.How should you complete the measure? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
FILTER
DATEADD
DIVIDE
Sales QoQ% =
IF(
ISFILTERED('financials'] [Date]),
ERROR("Uh oh"),
VAR PREV_QUARTER =
FILTER
(SUM('financials'] [Sales]),
DATEADD('financials'] [Date]),-1,QUARTER))
RETURN
DIVIDE ((SUM('financials'] [Sales]) - PREV_QUARTER), PREV_QUARTER)
)
SUM
DATEADD
DIVIDE
Sales QoQ% =
IF(
ISFILTERED('financials'] [Date]),
ERROR("Uh oh"),
VAR PREV_QUARTER =
SUM
(FILTER('financials'] [Sales]),
DATEADD('financials'] [Date]),-1,QUARTER))
RETURN
DIVIDE ((SUM('financials'] [Sales]) - PREV_QUARTER), PREV_QUARTER)
)
FIND
SUM
DIVIDE
Sales QoQ% =
IF(
ISFILTERED('financials'] [Date]),
ERROR("Uh oh"),
VAR PREV_QUARTER =
FIND
(SUM('financials'] [Sales]),
DATEADD('financials'] [Date]),-1,QUARTER))
RETURN
DIVIDE ((SUM('financials'] [Sales]) - PREV_QUARTER), PREV_QUARTER)
)
CALCULATE
DATEADD
DIVIDE
Sales QoQ% =
IF(
ISFILTERED('financials'] [Date]),
ERROR("Uh oh"),
VAR PREV_QUARTER =
CALCULATE
(SUM('financials'] [Sales]),
DATEADD('financials'] [Date]),-1,QUARTER))
RETURN
DIVIDE ((SUM('financials'] [Sales]) - PREV_QUARTER), PREV_QUARTER)
)
You are creating a Power BI model and report.You have a single table in a data model named Product. Product contains the following fields:✑ ID✑ Name✑ Color✑ Category✑ Total SalesYou need to create a calculated table that shows only the top eight products based on the highest value in Total Sales.How should you complete the DAX expression? To answer, drag the appropriate values to the correct targets. Each value 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.
Top 8 Products = CALCULATETABLE (8, 'Product', 'Product'[Total Sales], MAXX)
Top 8 Products = TOPN (8, 'Product', 'Product'[Total Sales], DESC)
Top 8 Products = TOPN (8, 'Product', 'Product'[Total Sales], MAXX)
Top 8 Products = CALCULATETABLE (8, 'Product', 'Product'[Total Sales], TOPN)
You are creating a sales report in Power BI for the NorthWest region sales territory of your company. Data will come from a view in a Microsoft SQL Server database. A sample of the data is shown in the following table:The report will facilitate the following analysis:✑ The count of orders and the sum of total sales by Order Date✑ The count of customers who placed an order✑ The average quantity per orderYou need to reduce data refresh times and report query times.Which two actions should you perform? Each correct answer presents part of the solution.
Set the data type for SalesOrderNumber to Decimal Number.
Remove the CustomerKey and ProductKey columns.
Remove the TaxAmt and Freight columns.
Filter the data to only the NorthWest region sales territory.
You are creating a Power BI model that contains a table named Store. Store contains the following fields.You plan to create a map visual that will show store locations and provide the ability to drill down from Country to State/Province to City.What should you do to ensure that the locations are mapped properly?
Change the data type of City, State/Province, and Country.
Set Summarization for City, State/Province, and Country to Don't summarize.
Set the data category of City, State/Province, and Country.
Create a calculated column that concatenates the values in City, State/Province, and Country.
You are building a data model for a Power BI report.You have data formatted as shown in the following table.You need to create a clustered bar chart as shown in the following exhibit.What should you do?
From Power Query Editor, split the Machine-User column by using a delimiter
From Power Query Editor, create a column that contains the last three digits of the Machine-User column.
In a DAX function, create two calculated columns named Machine and User by using the SUBSTITUTE function.
In a DAX function, create two measures named Machine and User by using the SUBSTITUTE function.
You need create a date table in Power BI that must contain 10 full calendar years, including the current year.How should you complete the DAX expression? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
YEAR
TODAY
CALENDAR
Date =
var var1 = [YEAR] (TODAY()))
return
CALENDAR (
DATE ( var1 - 9, 01, 01 ),
DATE ( var1, 12, 31 )
)
CALENDAR
TODAY
CALENDARAUTO
Date =
var var1 = [CALENDAR] (TODAY()))
return
CALENDARAUTO (
DATE ( var1 - 9, 01, 01 ),
DATE ( var1, 12, 31 )
)
TODAY
CALENDAR
CALENDARAUTO
Date =
var var1 = [TODAY] (CALENDAR()))
return
CALENDARAUTO (
DATE ( var1 - 9, 01, 01 ),
DATE ( var1, 12, 31 )
)
YEAR
CALENDAR
CALENDARAUTO
Date =
var var1 = [YEAR] (CALENDAR()))
return
CALENDARAUTO (
DATE ( var1 - 9, 01, 01 ),
DATE ( var1, 12, 31 )
)
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.
You have a Power BI report that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys:✑ Due Date✑ Order Date✑ Delivery DateYou need to support the analysis of sales over time based on all the date foreign keys.Solution: You create measures that use the USERELATIONSHIP DAX function to filter sales on the active relationship between the sales table and the date table.Does this meet the goal?
No
Yes
You have a Power BI report that contains a measure named Total Sales.You need to create a new measure that will return the sum of Total Sales for a year up to a selected date.How should you complete the DAX expression? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
Measure = CALCULATE ([TotalSales], TOTALTYD)
Measure = TOTALTYD ([TotalSales], 'Date'[Date])
Measure = TOTALTYD ([TotalSales], CALCULATE)
Measure = SUM ([TotalSales], CALCULATE)
You are modifying a Power BI model by using Power BI Desktop.You have a table named Sales that contains the following fields.You have a table named Transaction Size that contains the following data.You need to create a calculated column to classify each transaction as small, medium, or large based on the value in Sales Amount.How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value 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.
CALCULATE
AND
FILTER
Transaction Size =
VAR SalesTotal = 'Sales'[Sales]
VAR FilterSegment =
CALCULATE (
'Transaction Size',
AND (
'Transaction Size'[Min] <= SalesTotal,
'Transaction Size'[Max] >= SalesTotal
)
)
VAR Result =
FILTER( DISTINCT ('Transaction Size'[Transaction Size]), FilterSegment)
RETURN Result
CALCULATE
FILTER
SUM
Transaction Size =
VAR SalesTotal = 'Sales'[Sales]
VAR FilterSegment =
CALCULATE (
'Transaction Size',
FILTER (
'Transaction Size'[Min] <= SalesTotal,
'Transaction Size'[Max] >= SalesTotal
)
)
VAR Result =
SUM( DISTINCT ('Transaction Size'[Transaction Size]), FilterSegment)
RETURN Result
CALCULATE
AND
SUM
Transaction Size =
VAR SalesTotal = 'Sales'[Sales]
VAR FilterSegment =
CALCULATE (
'Transaction Size',
AND (
'Transaction Size'[Min] <= SalesTotal,
'Transaction Size'[Max] >= SalesTotal
)
)
VAR Result =
SUM( DISTINCT ('Transaction Size'[Transaction Size]), FilterSegment)
RETURN Result
SUM
AND
FILTER
Transaction Size =
VAR SalesTotal = 'Sales'[Sales]
VAR FilterSegment =
SUM (
'Transaction Size',
AND (
'Transaction Size'[Min] <= SalesTotal,
'Transaction Size'[Max] >= SalesTotal
)
)
VAR Result =
FILTER( DISTINCT ('Transaction Size'[Transaction Size]), FilterSegment)
RETURN Result
You have a Power BI report for the procurement department. The report contains data from the following tables.There is a one-to-many relationship from Suppliers to LineItems that uses the ID and Supplier ID columns.The report contains the visuals shown in the following table.You need to minimize the size of the dataset without affecting the visuals.What should you do?
Merge Suppliers and LineItems.
Remove the LineItems[Description] column
Remove the rows from LineItems where LineItems[Invoice Date] is before the beginning of last month.
Group LineItems by LineItems[Invoice ID] and LineItems[Invoice Date] with a sum of LineItems[Price].
You have a Power BI 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 load times.Which two actions will reduce the load times? Each correct answer presents part of the solution.
. Remove the rows in Posts in which Posts[Publish Date] is in the last seven days.
Remove the rows in Traffic in which Traffic[URL Visited] does not contain "blog"
Remove Traffic[IP Address], Traffic[Browser Agent], and Traffic[Referring URL].
Remove Posts[Full Text] and Posts[Summary]
You are creating a quick measure as shown in the following exhibit image.
You need to create a monthly rolling average measure for Sales over time.How should you configure the quick measure calculation? To answer, select the appropriate options.
Base value: TotalSales
Date: Date
Period: Month
Base value: TotalCost
Date: Date
Period: Month
Base value: TotalCost
Date: Date
Period: Years
Base value: TotalSales
Date: Date
Period: Years
You have the Power BI data model shown in the following exhibit.The Sales table contains records of sales by day from the last five years up until today’s date.You plan to create a measure to return the total sales of March 2021 when March 2022 is selected.Which DAX expression should you use?
Calculate (Sum(Sales[Sales]), PREVIOUSYEAR( dimDate[Date])
TOTALYTD (SUM(Sales[Sales]), dimDate[Date] )
Calculate (SUM(Sales[Sales]), SAMEPERIODLASTYEAR(dimDate[Date] ))
SUM(Sales[Sales])
You use Power BI Desktop to load data from a Microsoft SQL Server database.While waiting for the data to load, you receive the following error.You need to resolve the error.What are two ways to achieve the goal? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point.
Reduce the number of rows and columns returned by each query.
Split long running queries into subsets of columns and use Power Query to merge the queries.
Use Power Query to combine log running queries into one query.
Disable query folding on long running queries.
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 the query.You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.Solution: You split the IoT DateTime column into a column named Date and a column named Time.Does this meet the goal?
Yes
No
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 the 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 IoT GUID column and retain the IoT ID column.Does this meet the goal?
Yes
No
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 the query.You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.Solution: You change the IoT DateTime column to the Date data type.Does this meet the goal?
Yes
No
You have a Microsoft Power BI report. The size of PBIX file is 550 MB. The report is accessed by using an App workspace in shared capacity of powerbi.com.The report uses an imported dataset that contains one fact table. The fact table contains 12 million rows. The dataset is scheduled to refresh twice a day at 08:00 and 17:00.The report is a single page that contains 15 AppSource visuals and 10 default visuals.Users say that the report is slow to load the visuals when they access and interact with the report.You need to recommend a solution to improve the performance of the report.What should you recommend?
Change any DAX measures to use iterator functions.
Remove unused columns from tables in the data model.
Replace the default visuals with AppSource visuals.
Increase the number of times that the dataset is refreshed.
You have a Power BI data model that contains two tables named Products and Sales.A one-to-many relationship exists between the tables.You have a report that contains a report-level filter for Products.You need to create a measure that will return the percent of total sales for each product. The measure must respect the report-level filter when calculating the total.How should you complete the DAX measure? To answer, drag the appropriate DAX functions to the correct targets. Each function 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.
Percent of Product Sales =
VAR ProductSales = SUM('Sales'[Sales])
VAR AllSales =
CALCULATE SUM('Sales'[Sales]), FILTER 'Products'[Product]))
RETURN
DIVIDE (ProductSales, AllSales)
Percent of Product Sales =
VAR ProductSales = SUM('Sales'[Sales])
VAR AllSales =
CALCULATE SUM('Sales'[Sales]), ALL 'Products'[Product]))
RETURN
DIVIDE (ProductSales, AllSales)
Percent of Product Sales =
VAR ProductSales = SUM('Sales'[Sales])
VAR AllSales =
CALCULATE SUM('Sales'[Sales]), ALLSELECTED 'Products'[Product]))
RETURN
DIVIDE (ProductSales, AllSales)
Percent of Product Sales =
VAR ProductSales = SUM('Sales'[Sales])
VAR AllSales =
CALCULATE SUM('Sales'[Sales]), SELECTEDVALUE 'Products'[Product]))
RETURN
DIVIDE (ProductSales, AllSales)
You have a Power BI data model that analyzes product sales over time. The data model contains the following tables.A one-to-many relationship exists between the tables.The auto date/time option for the data model is enabled.You need to reduce the size of the data model while maintaining the ability to analyze product sales by month and quarter.Which two actions should you perform? Each correct answer presents part of the solution.NOTE: Each correct answer is worth one point.
Create a relationship between the Date table and the Sales table.
Disable the auto date/time option.
Create a Date table and select Mark as Date Table.
Disable the load on the Date table.
Remove the relationship between the Product table and the Sales table.
You have a Microsoft Power BI report. The size of PBIX file is 550 MB. The report is accessed by using an App workspace in shared capacity of powerbi.com.The report uses an imported dataset that contains one fact table. The fact table contains 12 million rows. The dataset is scheduled to refresh twice a day at 08:00 and 17:00.The report is a single page that contains 15 AppSource visuals and 10 default visuals.Users say that the report is slow to load the visuals when they access and interact with the report.You need to recommend a solution to improve the performance of the report.What should you recommend?
Implement row-level security (RLS).
Remove unused columns from tables in the data model.
Replace the default visuals with AppSource visuals.
Enable visual interactions.
You have a Power BI data model that contains a table named Stores. The table has the following columns:• Store Name• Open Date• Status• State• CityYou need to create a calculated column named Active Store Name that meets the following requirements:• When the value of the Status column is “A”, the value in the Store Name column must be returned.• When the value of the Status column is NOT “A”, the value in the Store Name column that is prefixed with "Inactive - " must be returned.How should you complete the DAX expression? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
Active Store Name = [SWITCH] ([Status]= "A",[Store Name], "Inactive" - [&] [Store Name])
Active Store Name = [SWITCH] ([Status]= "A",[Store Name], "Inactive" - [&&] [Store Name])
Active Store Name = [IF] ([Status]= "A",[Store Name], "Inactive" - [&&] [Store Name])
Active Store Name = [IF] ([Status]= "A",[Store Name], "Inactive" - [&] [Store Name])
You have a CSV file that contains user complaints. The file contains a column named Logged. Logged contains the date and time each complaint 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 transformation to extract the first 11 characters of the logged column.
Apply a transformation to extract the first 11 characters of the logged column.
Add a conditional column that outputs 2018 if the Logged column starts with 2018 and set the data type of the new column to Whole Number.
Create a column by example that starts with 2018-12-31 and set the data type of the new column to Date.
Apply a transformation to extract the last 11 characters of the Logged column and set the data type of the new column to Date.
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 the query.You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.Solution: You create a custom column that concatenates the IoT GUID column and the IoT ID column and then delete the IoT GUID and IoT ID columns.Does this meet the goal?
Yes
No
You have a Power BI model that contains a table named Employee. The table contains the following data.Each employee has one manager as shown in the ParentEmployeeID column.All reporting paths lead to the CEO at the top of the organizational hierarchy.You need to create a calculated column that returns the count of levels from each employee to the CEO.Which DAX expression should you use?
PATHLENGTH(PATH(Employee[EmployeeID],Employee[ParentEmployeeID]))
PATHITEM(PATH(Employee[EmployeeID],Employee[ParentEmployeeID]),1,INTEGER)
PATHCONTAINS(PATH(Employee[EmployeeID],Employee[ParentEmployeeID]),1)
PATH(Employee[EmployeeID],Employee[ParentEmployeeID])
You have a Microsoft Power BI report. The size of PBIX file is 550 MB. The report is accessed by using an App workspace in shared capacity of powerbi.com.The report uses an imported dataset that contains one fact table. The fact table contains 12 million rows. The dataset is scheduled to refresh twice a day at 08:00 and 17:00.The report is a single page that contains 15 AppSource visuals and 10 default visuals.Users say that the report is slow to load the visuals when they access and interact with the report.You need to recommend a solution to improve the performance of the report.What should you recommend?
Replace the default visuals with AppSource visuals.
Remove unused columns from tables in the data model.
Change the imported dataset to DirectQuery
Increase the number of times that the dataset is refreshed.
You have a CSV file that contains user complaints. The file contains a column named Logged. Logged contains the date and time each complaint 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?
Change the data type of the Logged column to Date.
Split the Logged column by using at as the delimiter.
Add a conditional column that outputs 2018 if the Logged column starts with 2018 and set the data type of the new column to Whole Number.
Apply the Parse function from the Date transformations options to the Logged column.
You have the Power BI data model shown in the following exhibit.You need to create a measure to count the number of product categories that had products sold during a selected period.How should you complete the DAX expression? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
Product Categories Sold =
CALCULATE (COUNT('Product'[ProductCategory]),'Date')
Product Categories Sold =
CALCULATE (DISTINCTCOUNT('Product'[ProductCategory]),'Date')
Product Categories Sold =
CALCULATE (DISTINCTCOUNT('Sales'[ProductID]),'Date')
Product Categories Sold =
CALCULATE (COUNT('Sales'[ProductID]),'Date')
