Model the data

A company has a Power BI dataset that contains a date table with columns: Date, Year, Month, Quarter, Day. The data model also includes a sales fact table with a SalesDate column. To enable time intelligence functions like TOTALYTD, what is the minimum requirement for the relationship between these tables?

A Power BI developer creates a star schema with a fact table Sales and dimension tables Customer, Product, Date. The relationship between Sales and Date is active. The developer wants to create a measure that calculates the total sales for the previous month relative to any selected month. Which DAX expression should the developer use?

A Power BI data model includes a table 'Orders' with columns OrderID, CustomerID, OrderDate, SalesAmount. The model also has a 'Date' table and a 'Customer' table. The relationships are: Orders[CustomerID] -> Customer[CustomerID] (many-to-one, single direction) and Orders[OrderDate] -> Date[Date] (many-to-one, single direction). A user creates a measure that sums SalesAmount and then filters by a slicer on Customer[City]. The slicer works correctly. However, when the user adds another slicer on Date[Year], the measure does not respect both slicers simultaneously. What is the most likely cause?

A Power BI developer needs to model data from two sources: an on-premises SQL Server database and a cloud-based Salesforce instance. The developer wants to create a star schema in Power BI. Which approach should the developer use to combine the data?

A Power BI developer has a fact table that contains sales data at the transaction level. The table includes columns: TransactionID, ProductID, CustomerID, DateKey, Quantity, UnitPrice, Discount, and SalesAmount. The developer wants to create a measure for total sales after discount. Which approach is best for performance and accuracy?

A Power BI developer is designing a data model for sales analysis. The model includes a Sales fact table and dimension tables: Product, Customer, Date, and Store. Which TWO design considerations are best practices for optimizing query performance?

A Power BI developer is building a data model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, ShipDate, SalesAmount. The developer wants to analyze orders by both order date and ship date. Which THREE actions should the developer take to properly model this scenario?

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model contains a large fact table with sales data. Users report that reports using this model are slow. Which design change would most improve query performance?

A data analyst is designing a star schema in Power BI. The model includes a table named 'Orders' with columns: OrderID, CustomerID, OrderDate, ProductID, Quantity, and SalesAmount. Which column should NOT be included in the fact table to maintain a proper star schema?

A Power BI developer is troubleshooting a report that uses a calculated table. The calculated table is defined as: 'Sales Summary = SUMMARIZE(Sales, Sales[ProductID], "Total Sales", SUM(Sales[Amount]))'. Users report that the 'Total Sales' column shows incorrect values when slicers are applied to the report. What is the most likely cause?

A company has a Power BI semantic model that uses Import mode. The model contains a table with 10 million rows. The data source is a SQL Server view that takes 5 minutes to execute. The scheduled refresh is set to every hour. What is the likely impact on refresh performance?

A data modeler is creating a Power BI semantic model for a retail company. The model includes a 'Products' dimension table with columns ProductID, ProductName, Category, and Subcategory. The 'Sales' fact table has columns ProductID, Date, Quantity, and Revenue. The modeler wants to ensure that users can filter by Category and Subcategory. Which relationship type should be created between Products and Sales?

A Power BI developer is designing a semantic model that will be used by multiple departments. The developer wants to ensure that the model follows best practices for performance and usability. Which TWO actions should the developer take?

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model includes a large fact table with 100 million rows. Users are experiencing slow report performance. Which THREE actions should the developer take to improve query performance?

What is the most likely cause of the error in the DAX query shown in the exhibit?

After loading the data using the Power Query M code shown in the exhibit, the model contains a table with 10,000 rows. However, when users filter by OrderDate in a report, the filter does not affect the aggregated TotalDue values. What is the most likely reason?

A company has a fact table with sales data and multiple dimension tables. They want to create a measure that calculates the total sales amount for the current year, but the measure returns incorrect results when used in a visual with a date hierarchy. What is the most likely cause?

A data model contains a table 'Sales' with columns: Date, ProductID, Quantity, Amount. There is a 'Products' table with columns: ProductID, ProductName, CategoryID. A measure 'Total Sales' = SUM(Sales[Amount]) returns correct values. However, when a user creates a visual with CategoryID from 'Products' and 'Total Sales', some categories show blank. What is the most likely cause?

A Power BI report uses a DirectQuery data source. The model includes a calculated column that uses the RELATED function to bring a value from another table. The report is performing slowly. What design change would most improve performance without compromising functionality?

A data model has a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. There is a 'Customers' table with columns: CustomerID, CustomerName. To analyze orders by customer, what is the best practice for modeling the relationship?

A company has a fact table 'Sales' with a column 'SalesAmount' and a dimension table 'Date'. They want to create a measure that calculates the running total of sales over time. The Date table is marked as a date table. Which DAX expression is correct?

Which TWO of the following are best practices for designing a data model in Power BI?

Which THREE of the following are valid reasons to create a calculated table in Power BI?

A company has a large fact table with sales data. The Sales table contains columns: OrderDate, ShipDate, DueDate, LineTotal, ProductKey, CustomerKey, TerritoryKey. The company needs to analyze sales by fiscal year (April 1 to March 31) and by calendar year. What is the recommended approach to model the date dimension?

You are a data analyst for a retail company. You are building a Power BI model to analyze inventory levels across multiple warehouses. The source data is a SQL Server database with two tables: Inventory (WarehouseID, ProductID, StockOnHand, ReorderPoint) and Product (ProductID, ProductName, Category, UnitPrice). The Inventory table has 500,000 rows, and Product has 10,000 rows. You import both tables into Power BI. You need to create a measure that calculates the total value of inventory (StockOnHand * UnitPrice) for products that are below their reorder point. You create the following measure: TotalValueBelowReorder = CALCULATE( SUMX(Inventory, Inventory[StockOnHand] * RELATED(Product[UnitPrice])), Inventory[StockOnHand] < Inventory[ReorderPoint] ) However, the measure returns an incorrect total. You suspect an issue with the filter context. What is the most likely cause of the incorrect result?

You are building a Power BI report for a sales team. You have a table named 'Sales' with columns: SalesDate, ProductID, Quantity, UnitPrice, Discount. You also have a 'Date' table with continuous date range. You create a relationship from Sales[SalesDate] to Date[Date]. You need to calculate the total sales amount (Quantity * UnitPrice - Discount). You write the following measure: TotalSales = SUMX(Sales, Sales[Quantity] * Sales[UnitPrice] - Sales[Discount]) The measure returns the correct total. However, when you slice by month from the Date table, the total does not change. What is the most likely cause?

You are building a Power BI model for a logistics company. You have a table named 'Shipments' with columns: ShipmentID, OriginCity, DestinationCity, Weight, Cost, ShipDate, DeliveryDate. You also have a 'City' table with columns: CityName, State, Region. You create relationships: Shipments[OriginCity] to City[CityName] and Shipments[DestinationCity] to City[CityName]. Both relationships are active and many-to-one. You create a measure to calculate total cost: TotalCost = SUM(Shipments[Cost]) When you use a slicer on City[State], you expect to filter shipments where either the origin or destination city is in that state. However, the filter only applies to the origin city due to the active relationship. You need to modify the model so that a single slicer on City[State] filters shipments where either origin or destination is in the selected state. What is the best approach?

A company has a Power BI semantic model with a table named 'Sales' that contains columns: OrderDate, ShipDate, Quantity, and Revenue. The company wants to create a measure that calculates the total revenue for orders shipped within 7 days of the order date. Which DAX expression should be used?

You are designing a Power BI semantic model for a retail company. The model must support reporting on sales by product, store, and date. You need to decide on the modeling approach. Which TWO actions should you take? (Select exactly two.)

You are reviewing a Power Query M script used to create a table in Power BI. The script imports data from SQL Server, filters for orders in 2022, groups by ProductID to sum revenue, sorts descending, and takes the top 10. However, the table loads slowly. You need to improve performance. Which change should you make?

Drag and drop the steps to configure Row-Level Security (RLS) in Power BI Desktop into the correct order.

Drag and drop the steps to create a date table in Power BI Desktop using DAX into the correct order.

Drag and drop the steps to create a quick measure in Power BI Desktop into the correct order.

Match each Power BI component to its purpose.

Match each Power BI service feature to its description.

Match each Power BI security feature to its purpose.

You are creating a star schema in Power BI. You have a fact table named Sales with columns: Date, ProductID, CustomerID, Quantity, and UnitPrice. You need to create a relationship between Sales and a Date dimension. Which column in the Date dimension should be used as the key to relate to the Date column in Sales?

You have a Power BI data model with a table named Products that contains columns ProductID, ProductName, and CategoryID. You also have a table named Categories with CategoryID and CategoryName. You want to ensure that when a user filters by a category, all products in that category are shown, even if the product has no sales. What type of relationship should you create between Products and Categories?

You are building a Power BI report that uses a DirectQuery connection to a SQL Server database. You need to reduce the amount of data transferred to Power BI when users interact with visuals. What should you do?

You have a Power BI model with a table named Orders that contains columns OrderDate, ShipDate, and CustomerID. You need to create a calculated column that computes the number of days between OrderDate and ShipDate. Which DAX expression should you use?

You are designing a Power BI data model that includes a table named Sales with 10 million rows. You need to create a relationship between Sales and a Product dimension table. The Product table has 10,000 rows. Which configuration will provide the best query performance?

You are modeling data in Power BI that includes a table named SurveyResponses with columns: ResponseID, QuestionID, RespondentID, and AnswerText. Each respondent answers multiple questions. You need to create a measure that counts the number of unique respondents who answered a specific question. Which DAX measure should you use?

You have a Power BI model with a table named Sales that includes columns: OrderDate, Amount, and CustomerID. You need to create a measure that returns the total sales amount for the previous month based on the current filter context. Which DAX expression should you use?

You have a Power BI data model with a table named Employees that includes columns: EmployeeID, ManagerID, and EmployeeName. You need to create a hierarchy that shows the reporting structure. Which type of relationship is required?

You are reviewing the relationships in a Power BI data model as shown in the exhibit. The model has tables: Sales, Product, Customer, and Category. You need to evaluate the performance impact of the current configuration. Which relationship is most likely to cause performance issues?

You are analyzing a DAX query as shown in the exhibit. You need to determine the result set. The model contains tables: Date, Product, and Sales with relationships. Which statement accurately describes the output?

You are reviewing the partition configuration for a Power BI Import model as shown in the exhibit. The table Sales is partitioned by year. You need to modify the model to improve incremental refresh performance. What change should you make?

You are designing a Power BI data model for a sales analysis. The model includes a table named Sales with columns: OrderID, OrderDate, CustomerID, ProductID, Quantity, UnitPrice. You need to create a star schema. Which TWO tables should you create as dimension tables?

You have a Power BI data model with a table named Employees that contains: EmployeeID, ManagerID, Department, and Salary. You need to create a parent-child hierarchy for the reporting structure. Which THREE actions should you perform?

You are creating a Power BI report that uses a table named Orders with columns: OrderID, OrderDate, ShipDate, and Status. You need to create a calculated table that contains one row per month with the total number of orders shipped in that month. Which TWO steps should you take?

You have a Power BI data model with a table named Sales that includes columns: ProductID, SalesAmount, and SalesDate. You need to create a measure that calculates the total sales amount for the current quarter and compares it to the previous quarter. Which THREE DAX functions should you use?

You are designing a data model in Power BI that includes a fact table called 'Sales' and dimension tables 'Customer', 'Product', and 'Date'. The 'Sales' table contains columns: 'SalesID', 'CustomerID', 'ProductID', 'DateKey', 'Quantity', and 'Amount'. You need to ensure that the model follows star schema best practices and that filters from the 'Customer' table propagate correctly to the 'Sales' table. What should you do?

You have a Power BI data model with a table 'Orders' that has columns: 'OrderID', 'OrderDate', 'CustomerName', 'Region', 'Product', 'Quantity', 'UnitPrice'. You want to create a measure that calculates total sales amount. Which DAX expression should you use?

You are modeling data from an Azure SQL Database into Power BI. The source table 'Sales' contains 10 million rows. You need to ensure that the data model supports fast query performance for a report that shows sales by month and product category. The report uses a slicer for year. What is the best practice for improving performance?

You have a Power BI model with a table 'Employees' that includes columns: 'EmployeeID', 'ManagerID', 'Name'. You need to create a hierarchy that shows the reporting structure. What should you do first?

You are building a data model for a retail company. The 'Sales' fact table has a column 'Discount' that is a percentage (0 to 1). You create a measure 'Total Discount Amount' = SUM(Sales[Discount]) * SUM(Sales[Quantity]) * SUM(Sales[UnitPrice]). However, the measure returns incorrect results when multiple discount percentages exist in the same filter context. What is the issue?

You have a Power BI data model with a 'Date' table that contains continuous dates from January 1, 2020, to December 31, 2025. The 'Sales' table has a relationship with the 'Date' table. You need to create a measure that calculates the total sales for the last 12 months from the current context. Which DAX function should you use?

Which TWO of the following are best practices for designing a star schema in Power BI?

Which THREE of the following are valid considerations when using Power BI DirectQuery mode?

Which TWO of the following are valid methods to create a date table in Power BI?

Which THREE of the following are benefits of using a calculated column over a measure in Power BI?

Which TWO of the following are true about the Power BI composite model?

Which THREE of the following are valid data types in Power BI?

You are building a star schema model in Power BI. You have a fact table of sales transactions and dimension tables for Date, Customer, Product, and Store. The Date table contains a column 'FiscalYear' that you want to use for time intelligence calculations. What is the best practice for handling the Date relationship?

You are importing data from a SQL Server database into Power BI. The source table has a column 'OrderDate' of type DATETIME. You want to filter data based on the date only, ignoring time. What is the most efficient approach?

Refer to the exhibit. The DAX measure 'Sales YTD' is defined as shown. The model has a Date table marked as a date table and a relationship to Sales[OrderDate]. However, the measure returns BLANK for all months except December. What is the most likely cause?

You are designing a Power BI model that includes a fact table with sales data and a dimension table for customers. Each customer can have multiple addresses, but you only need the primary address for analysis. The source system has a 'CustomerAddress' table with a 'IsPrimary' flag. What is the best approach to bring this into the model?

You have a Power BI model with a fact table 'Sales' and a dimension table 'Product'. The Product table contains columns: ProductID, ProductName, Category, and Subcategory. You want to create a hierarchy for drill-down in reports: Category > Subcategory > ProductName. What is the correct way to define this hierarchy?

Refer to the exhibit. You are configuring a Power BI data model for a workspace containing a semantic model with sensitive salary data. The JSON policy above is applied. A viewer reports that they can see the EmployeeSalaries table in the report. What is the most likely reason?

You are modeling data from multiple sources: a SQL Server database for sales, an Excel file for budget, and a SharePoint list for product targets. You need to combine these into a single Power BI report. What is the recommended approach for handling data refresh?

You have a fact table 'Orders' with columns: OrderID, CustomerID, OrderDate, SalesAmount. You also have a 'Calendar' table with Date, Year, Month, Quarter. The Calendar table is marked as a date table. You want to calculate total sales for the current month. Which DAX measure should you use?

Refer to the exhibit. You are reviewing a DAX measure for month-over-month sales growth. The measure returns BLANK for all months. What is the likely issue?

Which TWO of the following are best practices for designing a Power BI data model?

Which THREE of the following are valid reasons to use a composite model (mixed storage mode) in Power BI?

Which TWO of the following are true about calculated columns in Power BI?

Refer to the exhibit. You apply the above RLS rule to a semantic model. The rule is intended to restrict sales data by the user's region, which is stored in the user's email domain (e.g., user@west.contoso.com). However, the rule does not filter any rows. What is the most likely issue?

You have a Power BI model with a large fact table (100 million rows) and several dimension tables. You need to improve query performance for a report that uses a date slicer. The report currently takes 10 seconds to load. What is the most effective optimization?

You are modeling data from a source that includes a column 'FullName' (e.g., 'John Doe'). You want to create separate 'FirstName' and 'LastName' columns for analysis. What is the most efficient way?

You need to create a calculated column that categorizes sales amounts into 'Low', 'Medium', and 'High' based on thresholds. Which DAX expression should you use?

You have a star schema with a Sales fact table and a Date dimension. You need to calculate year-to-date sales that reset each fiscal year starting July 1. Which measure is correct?

You need to create a relationship between two tables in Power BI. Both tables contain a column named 'ProductID', but the values in one table are integers and in the other are text. What should you do first?

Refer to the exhibit. You are implementing row-level security (RLS) in Power BI. The JSON policy above is applied to the 'Sales' table. The user is in the 'SalesRegion' role. Which rows will the user see?

You have a table with columns 'Date', 'Sales', and 'Quantity'. You need to create a measure that calculates the average sales per transaction. Which DAX measure should you use?

You are building a Power BI model with a fact table and multiple dimension tables. You want to enforce a rule that each fact row must have a matching row in a related dimension. Which modeling technique should you use?

Refer to the exhibit. You have a Sales table. You create a measure: TotalSales = SUM(Sales[SalesAmount]). You then create another measure: SalesAboveAverage = CALCULATE([TotalSales], FILTER(Sales, Sales[SalesAmount] > AVERAGE(Sales[SalesAmount]))). What is the value of SalesAboveAverage?

You have two tables: 'Orders' and 'Customers'. You want to create a relationship where each order is linked to one customer, but a customer can have many orders. Which cardinality should you choose?

You have a Power BI model with a 'Date' table marked as a date table. You need to create a measure that calculates the running total of sales over the last 12 months. Which DAX function should you use?

Which TWO actions are best practices for optimizing Power BI data models?

Which THREE factors should you consider when designing a star schema in Power BI?

Which TWO DAX functions can be used to filter data in a measure?

Refer to the exhibit. A user is a member of both 'Manager' and 'Executive' roles. Which rows will the user see?

You have a table with columns 'Product', 'Category', and 'Sales'. You want to create a hierarchy that allows users to drill down from Category to Product. Which is the correct order to create the hierarchy?

You are modeling data for a retail company. You have a 'Transactions' fact table with millions of rows. You need to improve query performance for a report that filters by 'Store' and 'Date'. Which action will have the most impact?

You are designing a star schema for a sales data model. Which table should be defined as a dimension table?

You have a Power BI model with a fact table 'Sales' and dimensions 'Customer', 'Product', 'Date'. You need to enforce that every fact row has a valid CustomerKey. Which approach enforces referential integrity in Power BI?

You need to create a calculated column that categorizes products as 'Low', 'Medium', or 'High' based on the 'UnitPrice' column. Which DAX function should you use?

You have a Power BI model with a date table. You need to ensure that time intelligence functions like TOTALYTD work correctly. What is the most important requirement for the date table?

Refer to the exhibit. You have the model shown. The active relationship is between OrderDate and Date. You create the measure TotalShipments. What does this measure calculate?

You have a Power BI model containing a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. You need to create a measure that calculates the total amount from the previous year. Which DAX function should be used?

You are modeling a many-to-many relationship between 'Student' and 'Class' tables. Which approach should you use in Power BI to handle this?

You have a fact table 'Transactions' with 100 million rows. You need to reduce the model size without losing detail. Which action is most effective?

You have a Power BI model with a table 'Sales' and a related 'Product' table. You want to count the number of distinct products sold. Which DAX expression should you use?

Which TWO actions can improve performance of a Power BI DirectQuery model?

Which THREE are best practices for designing a star schema in Power BI?

Which TWO DAX functions can be used to create a calculated table in Power BI?

Refer to the exhibit. You apply the row-level security (RLS) policy shown to the Sales table. Which rows will be visible to users?

Refer to the exhibit. What is the result of this DAX expression?

Refer to the exhibit. You write this Power Query M code to import data. What does the final step do?

A data model contains a Date table and a Sales table. You need to create a measure that calculates total sales for the previous year. Which DAX function should you use?

You have a Power BI data model with a fact table and multiple dimension tables. You notice that many-to-many relationships cause ambiguous results. What is the best practice to resolve this?

You are designing a star schema for a sales analysis report. The source data includes Order Details, Products, Customers, and Dates. Which table should be the fact table?

You need to create a calculated column that categorizes sales amounts into 'Low', 'Medium', and 'High' based on thresholds. Which DAX function should you use?

You have a data model with a Sales table and a Date table. You create a measure: Total Sales = SUM(Sales[Amount]). When you add a slicer for Date[Year], the measure does not filter correctly. What is the most likely cause?

You are designing a Power BI data model for a retail chain. You have three fact tables: Sales, Inventory, and Returns. Which modeling approach is best for cross-filtering between these facts?

You need to create a hierarchy in Power BI that allows drilling down from Year to Quarter to Month. What is the correct approach?

You have a Power BI data model with a table that contains duplicate rows. You want to remove duplicates in Power Query. Which transformation should you use?

You have the DAX expression shown. What does this expression return?

Which TWO of the following are valid DAX functions for time intelligence? (Select two.)

Which THREE of the following are benefits of using a star schema in Power BI? (Select three.)

Which TWO of the following are valid methods to handle slowly changing dimensions (SCD) Type 2 in Power Query? (Select two.)

You have the Power Query M code shown. What is the result of this query?

You have a data model with two relationships between Sales and Date: one active (OrderDateKey) and one inactive (ShipDateKey). The DAX expression uses USERELATIONSHIP(Sales[DateKey], 'Date'[DateKey]). Which date will be used for filtering?

You have a Power BI data model with a Sales table and a Product table. You want to create a measure that calculates the percentage of total sales for each product category. Which DAX pattern should you use?

You are building a Power BI data model with a sales table containing millions of rows. You need to design a date dimension table to support time intelligence calculations. What is the best practice for creating the date table?

You are modeling data for a retail company. The fact table contains sales transactions with columns: OrderDate, ProductID, CustomerID, Quantity, and SalesAmount. You also have dimension tables: Date, Product, Customer. The Date table has a relationship to the fact table on OrderDate, and the Customer table has a relationship to the fact table on CustomerID. However, you need to support analysis by both OrderDate and ShipDate. What is the recommended approach?

You have a Power BI model with a fact table and several dimension tables. You need to ensure that when a filter is applied to a dimension table, it also filters related rows in other dimension tables through the fact table. Which type of relationship direction should you configure?

You are reviewing a Power BI model definition in JSON. The Sales table contains a ProductID column but the Product table does not have a ProductID column; instead it has a ProductID column with dataType string. What issue will occur when you try to create a relationship?

You have a Power BI model with a table named 'Orders' that contains columns: OrderID, CustomerID, OrderDate, and TotalAmount. You need to create a measure that calculates the total sales amount for orders placed in the last 30 days, but only for customers who have placed more than 5 orders in total. What is the most efficient DAX measure?

You are modeling data for a sales analysis. You have a fact table 'Sales' and a dimension table 'Date'. You need to create a relationship between 'Sales[OrderDate]' and 'Date[Date]'. The 'Date' table contains dates from January 1, 2020 to December 31, 2025. The 'Sales' table contains orders from January 1, 2021 to June 30, 2024. Which relationship cardinality should you use?

You have a Power BI data model with a table named 'Sales' and a table named 'Targets'. The 'Sales' table contains daily sales data, and the 'Targets' table contains monthly sales targets for each product category. You need to create a measure that calculates the percentage of target achieved for the current month. The relationship between 'Sales' and 'Targets' is on CategoryID and Month. However, the 'Sales' table has a granularity of day, while 'Targets' has month. What issue might you encounter when creating this measure?

You are designing a data model for a report that shows sales by region and product category. The source data includes a table 'Sales' with columns: Region, Category, SalesAmount. You also have separate tables 'Regions' and 'Categories' that contain additional attributes. You need to create a star schema. What should you do with the 'Region' and 'Category' columns in the 'Sales' table?

You are reviewing a Power BI model definition with incremental refresh policy. The Sales table has an incremental refresh policy that refreshes the last 365 days. However, the report shows data for dates beyond 365 days ago. What is the most likely reason?

Which TWO actions should you take when designing a data model that includes a fact table with a large number of rows and multiple dimension tables? (Select exactly 2.)

Which THREE considerations are important when implementing row-level security (RLS) in Power BI? (Select exactly 3.)

Which TWO are valid reasons to use a star schema design in Power BI? (Select exactly 2.)

Which THREE are best practices for managing relationships in Power BI? (Select exactly 3.)

You have a DAX measure that sums the Amount column for rows where Quantity is greater than 10. The Sales table has 10 million rows. What is a potential performance issue with this measure?

You have a Power BI data model that uses a DirectQuery connection to a SQL Server database. The model contains a fact table 'OrderDetails' with 50 million rows and a dimension table 'Products' with 10,000 rows. You need to create a measure that calculates the average order quantity per product. What is the best approach to optimize performance?

You are building a star schema in Power BI. A fact table contains sales transactions with columns: OrderID, CustomerID, ProductID, Quantity, UnitPrice, Discount, and OrderDate. You need to create a dimension table for customers. Which columns should be included in the Customer dimension?

You have a Power BI model with a table 'Sales' and a table 'Date'. The relationship between them is many-to-one (Sales[OrderDate] -> Date[Date]). You notice that when you filter by Date[Year], some sales rows are not included. What is the most likely cause?

You need to create a calculated column in Power BI that categorizes sales amounts as 'Low', 'Medium', or 'High' based on the value. The column should be evaluated row by row. Which DAX function should you use?

You are reviewing a Power BI model definition in TMSL. The model has incremental refresh configured with two partitions. When the model refreshes on July 1, 2024, which data will be refreshed in Partition1?

You are designing a Power BI data model that includes a Sales table and a Product table. The Product table contains a column 'Category' with values like 'Electronics', 'Clothing', etc. You need to create a measure that calculates the total sales amount for the 'Electronics' category only. Which DAX expression should you use?

You have a Power BI dataset that includes a table 'Orders' with columns: OrderDate, ShipDate, CustomerID, and SalesAmount. You need to create a calculated column that shows the number of days between OrderDate and ShipDate. Which DAX expression should you use?

You are examining a Power BI model definition. The Date table is generated via Power Query M code. The partition mode is 'import'. What will happen when the dataset refreshes after December 31, 2025?

You are modeling a many-to-many relationship between 'Students' and 'Courses' via a junction table 'Enrollments'. You need to create a measure that counts the number of students enrolled in at least one course. The relationship between Students and Enrollments is one-to-many, and between Courses and Enrollments is one-to-many. What DAX measure should you use?

You need to create a hierarchy in Power BI that allows users to drill down from Year to Quarter to Month. Which of the following actions is required?

Which TWO of the following are valid reasons to use a calculated table instead of a calculated column in Power BI?

Which THREE of the following are best practices when designing a Power BI data model for performance?

Which TWO of the following are valid DAX functions for time intelligence?

You are analyzing a DAX query. What is the purpose of the 'Filter Context' column in the result?

You have a Power BI model with a table 'Sales' and a separate 'Calendar' table. The relationship between Sales[OrderDate] and Calendar[Date] is active. You need to create a measure that calculates the total sales for the previous month relative to the current filter context. Which DAX expression should you use?

You need to create a relationship between two tables in Power BI. Table A has a column 'ProductID' with unique values. Table B has a column 'ProductID' with duplicate values. Which relationship cardinality should you choose?

You have a Power BI semantic model that imports sales data from Azure SQL Database. The model includes a date table and a fact table with a column 'SalesAmount'. You need to create a measure that calculates the total sales amount only for the last 30 days relative to the report date. Which DAX expression should you use?

Refer to the exhibit. You are managing a Power BI workspace and applying dataset permissions via the XMLA endpoint. The JSON policy shows permissions for two users on the 'Sales' dataset. user1 has Viewer role, user2 has Reshare role. The dataset has row-level security (RLS) defined. Which statement is true about the permissions?

You are modeling a fact table that contains sales transactions with columns: OrderDate, ShipDate, SalesAmount, CustomerKey. You need to create a relationship to a date table. The date table has a single Date column. Which relationship should you create for the most accurate time-based analysis?

Refer to the exhibit. You are using DAX Studio to profile a Power BI semantic model. The query above returns a table with sales totals by year and product category. However, you notice that the results do not include rows for years or categories with no sales. Which DAX function should you use to ensure all combinations of year and category appear, even with blank sales?

You are designing a Power BI semantic model for an e-commerce company. You have a fact table with OrderID, CustomerID, OrderDate, and SalesAmount. You also have a Customers table with CustomerID, CustomerName, and CustomerSegment. You need to ensure that filters on CustomerSegment propagate to the SalesAmount measure. What should you do?

Your organization uses Power BI with large datasets from Azure Synapse Analytics. You need to reduce model size and improve query performance. You decide to use aggregations. Which type of aggregation table is most appropriate for pre-aggregating data at the year and category level?

Refer to the exhibit. You have defined row-level security (RLS) in a Power BI semantic model using Role-level security. The JSON shows three rules for the 'Sales' and 'Targets' tables. The user 'john@contoso.com' belongs to this role. John's manager column in the Sales table has the value 'john@contoso.com'. What data will John see when he queries the model?

You are building a Power BI semantic model that includes a Date table. Which of the following is a best practice for creating a Date table?

Refer to the exhibit. A Power BI developer wrote the DAX measure above to calculate year-over-year sales growth. When tested in a matrix visual with Year on rows and Month on columns, the measure returns incorrect results for the month of February in leap years. What is the likely cause?

You have a Power BI semantic model with a fact table containing sales data at the transaction level. You need to create a measure that calculates the number of distinct customers who made a purchase in the current period and also made a purchase in the previous period. Which DAX pattern should you use?

Which TWO of the following are valid reasons to create a separate date table in a Power BI semantic model? (Select two.)

Which TWO of the following are best practices when designing star schemas in Power BI? (Select two.)

Which THREE of the following are valid ways to model a many-to-many relationship between tables in Power BI? (Select three.)

Which THREE of the following are considerations when implementing row-level security (RLS) in Power BI? (Select three.)

Which TWO of the following are valid DAX functions for modifying filter context within a measure? (Select two.)

You are designing a data model for a sales analysis report. The source data includes a table named 'Sales' with columns: OrderDate, CustomerID, ProductID, Quantity, and SalesAmount. You need to create a date table to support time intelligence calculations. Which approach should you use?

You are building a Power BI model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, and TotalAmount. You also have a table 'Customers' with columns: CustomerID, CustomerName, and Segment. You need to create a relationship between Orders and Customers on CustomerID. Which relationship configuration should you choose to ensure that filtering Customers by Segment correctly filters Orders?

You have a Power BI data model that contains a table 'Sales' with columns: Date, ProductID, and Revenue. You also have a 'Products' table with columns: ProductID, ProductName, and Category. You want to create a measure that calculates total revenue for the current year. Which DAX expression should you use?

You are modeling data for a retail company. The source data contains a table 'Transactions' with columns: TransactionID, StoreID, ProductID, Quantity, and SalesAmount. You need to create a star schema in Power BI. What should you do with the TransactionID column?

You have a Power BI model with a table 'Sales' that contains columns: Date, SalespersonID, and Amount. You have a 'Salespeople' table with columns: SalespersonID, Name, and Region. You need to create a measure that calculates the total sales amount for the current region, but only for salespeople who have made at least one sale in the current month. Which DAX expression achieves this?

You are creating a Power BI report that requires a many-to-many relationship between 'Product' and 'Customer' tables. What is the recommended way to implement this?

You have a Power BI model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, and TotalAmount. You have a 'Customers' table with columns: CustomerID, CustomerName, and Country. You need to create a measure that calculates the total sales amount for customers who have placed orders in the last 30 days. Which DAX measure should you use?

You are designing a data model for a financial analysis report. The source data includes a 'Budget' table with columns: Department, Account, Month, and BudgetAmount. The 'Actuals' table has the same structure. You need to create a combined measure that shows the variance (Actual - Budget) for each Department and Account. What is the best approach?

You have a Power BI model with a table 'Sales' that contains a column 'OrderDate'. You need to create a calculated column that extracts the year from OrderDate. Which DAX expression should you use?

Which TWO of the following are valid reasons to use a calculated table in Power BI instead of a table from the source?

Which THREE of the following are best practices for designing a Power BI data model?

Which TWO of the following are valid DAX functions for creating a calculated table?

You have the above measure in a Power BI model. The 'Date' table is marked as a date table and has a relationship to Sales[OrderDate]. The measure returns blank for all months. What is the most likely cause?

You have the above Power Query M script. What is the result of this transformation?

You have the above calculated column in a Power BI model. Some rows show blank values for Profit Margin even though Profit and SalesAmount are not blank. What is the most likely cause?

You are building a star schema in Power BI. Which table design best supports filtering a sales fact table by product category?

You have a date table with columns: Date, Year, Month, Quarter, Day. To enable time intelligence functions like TOTALYTD, what is the minimum requirement?

You need to create a calculated column that categorizes products based on price: 'Low' (<$10), 'Medium' ($10-$50), 'High' (>$50). Which DAX expression should you use?

When creating a many-to-many relationship between two tables, what is a common approach to model this in Power BI?

Which TWO actions are valid for improving query performance in DirectQuery mode?

Which THREE considerations are important when designing a date table for time intelligence?

Which TWO approaches can you use to implement row-level security (RLS) in Power BI?

You have a table with a column 'Date' and a measure 'Total Sales'. You want to calculate the cumulative total of sales over time. Which DAX function should you use?

You need to create a measure that calculates the average sales per transaction. The 'Sales' table has columns 'TransactionID' and 'Amount'. Which DAX expression is correct?

Which THREE factors can cause a DAX measure to return BLANK unexpectedly?

You have a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. You want to create a measure that shows the total number of orders. Which DAX function should you use?

You are designing a data model for a report that shows sales by product category and by month. Which table configuration is most efficient?

You are building a star schema in Power BI. Your fact table contains sales data at the transaction level. Which of the following is the best practice for modeling the date dimension to support time intelligence functions like year-to-date (YTD) calculations?

You have a Power BI model with tables: Sales (DateKey, Amount) and Date (DateKey, Year, Month, Day). The measure above is intended to show sales for the current year ignoring any filters on date. However, when placed in a matrix with Month on rows, it returns the same value for every month. What is the most likely reason?

You are designing a data model that will support self-service analytics. You have a Sales table with over 100 million rows. Which of the following modeling approaches would provide the best query performance while maintaining a user-friendly experience?

You have a Power BI model where the Sales table is filtered by a Customer dimension. Users report that when they filter a measure from the Customer table (e.g., Customer Count), it does not affect the Sales visual. What is the most likely cause?

You are creating a Power BI report that uses a composite model (DirectQuery for large tables and Import for small dimension tables). You want to ensure that measures referencing the DirectQuery tables are responsive. Which of the following design choices should you avoid?

You are modeling data for a sales analysis. The Sales table includes a column 'ProductID' and a related Products table. You need to create a measure that calculates the total sales amount only for products in the 'Electronics' category. Which DAX measure should you use?

You are loading data into Power BI. The above Power Query script connects to a SQL Server database and loads aggregated sales by customer. However, the report requires the ability to drill down to individual transactions for a selected customer. What is the best approach to meet this requirement without losing the performance benefit of aggregation?

You have a Power BI data model with a table 'Orders' containing columns: OrderID, CustomerID, OrderDate, Amount. You want to create a measure that calculates the running total of sales over time, ordered by OrderDate. Which DAX expression should you use?

You are designing a Power BI model for a multinational company. The fact table contains sales data in multiple currencies. You need to convert all amounts to a single reporting currency (USD) using exchange rates from a separate table. What is the recommended approach?

Which TWO of the following are best practices for modeling many-to-many relationships in Power BI?

Which THREE of the following are valid reasons to use a calculated column instead of a measure in Power BI?

Which TWO of the following are true about using the 'Mark as Date Table' feature in Power BI?

You run the above DAX query in DAX Studio. The result set shows a row for each Category and Year combination, but the Total Sales and Total Cost columns are both blank. What is the most likely reason?

You are modeling a data source that includes a table with columns: EmployeeID, ManagerID. You need to create a hierarchy that shows the reporting structure. Which Power BI feature should you use?

You are reviewing a Power BI model definition. The Sales table has a partition with an M expression. You need to ensure that the table can be refreshed incrementally. Which additional property must be set?

You are building a star schema in Power BI. The Sales table contains sales amount, quantity, and discount. You need to create a relationship between Sales and a Date table. The Date table must have a one-to-many relationship with Sales, and all date filters must show sales even if no sales occurred on that date. Which relationship configuration should you use?

You have a Power BI semantic model with a fact table 'Orders' and dimension tables 'Customer', 'Product', and 'Date'. The model uses DirectQuery against Azure Synapse. Users report that a measure calculating Year-over-Year growth returns incorrect values for the current year when no data exists for the prior year. Which DAX modification ensures the measure returns blank instead of an incorrect value?

You are designing a Power BI data model for a retail company. The model must include a table with product prices that change over time. Which table design should you use to support historical price analysis?

You are modeling data from multiple sales regions. Each region has a unique ID, but region names might be spelled inconsistently (e.g., 'North America' vs. 'N. America'). You need to create a single dimension table for regions. What is the best practice to handle this?

You have a Power BI model with a measure that calculates total sales using SUMX over a filtered table. The measure performs slowly. Which change will most likely improve performance without altering business logic?

You are designing a data model for a sales analysis. The 'Sales' fact table contains columns: OrderDate, ShipDate, Amount, Quantity. You need to analyze sales by both order date and ship date. What is the best practice to model the dates?

Your Power BI model includes a calculated column that concatenates first and last name. Users report that the column shows blank for some rows. The data source has no nulls. What is the most likely cause?

You are modeling a fact table with granularity at the order line level. The table includes columns: OrderID, ProductID, Quantity, UnitPrice, Discount. You need to create a measure for total revenue considering discounts (Quantity * UnitPrice * (1 - Discount)). Some orders have no discount (null). What is the correct DAX for this measure?

You need to create a relationship between two tables where one table has duplicate values on the key column. Which cardinality should you choose?

You are designing a Power BI data model for a manufacturing company. Which TWO practices help optimize performance when using DirectQuery?

You are modeling data with a many-to-many relationship between 'Student' and 'Class' tables. Which THREE configurations can handle this scenario?

You are creating a star schema in Power BI. Which TWO tables are typically dimension tables?

You are a data analyst at a global retail company. You are building a Power BI semantic model to analyze sales performance across 50 countries. The data source is an Azure SQL Database with tables: Sales (SalesID, ProductID, StoreID, DateKey, Quantity, Amount), Products (ProductID, ProductName, CategoryID), Stores (StoreID, StoreName, CountryID), Countries (CountryID, CountryName), and Dates (DateKey, Date, Year, Month, Quarter). The model must support: 1) Hierarchical drill-down from Year to Quarter to Month. 2) Slicers for Country and Product Category. 3) Measures for Total Sales, Year-over-Year growth, and Moving Average (last 12 months). 4) The ability to filter by date range (e.g., last 3 months) while preserving the ability to show YoY growth for the selected period. The database contains 500 million rows in the Sales table. The company has strict performance requirements: report pages must load within 5 seconds. You need to design the model in Power BI Desktop. Which approach should you take?

You are a Power BI developer for a healthcare organization. You are building a semantic model to analyze patient readmission rates. The data warehouse contains: Admissions (AdmissionID, PatientID, AdmitDate, DischargeDate, DiagnosisCode, HospitalID) and Readmissions (ReadmissionID, PatientID, ReadmitDate, Reason). You need to create a measure that calculates the readmission rate within 30 days of discharge. The measure must consider only the first readmission per patient per admission. You also need to create a visual that shows the trend of readmission rates over time, allowing users to filter by diagnosis. The model will be used by 200 analysts and must refresh daily. Which DAX measure should you create?

You are a data analyst for a university. You need to build a Power BI report to analyze student enrollment by program and year. Data sources: a CSV file with student enrollment records (StudentID, Program, EnrollmentYear, Status) and an Excel file with program details (ProgramCode, ProgramName, Faculty). The CSV file contains 1 million rows. The report must allow users to filter by faculty and program, and see a bar chart of enrollment counts by year. You need to design the data model. What should you do?

You are building a star schema in Power BI. The fact table contains sales transactions. Which of the following should be stored in a dimension table?

You have a Power BI data model with a table named 'Sales' that has a many-to-many relationship with 'Product' through a bridge table. When creating a measure to calculate total sales by product, you notice the totals are double-counting. What is the most likely cause?

You need to create a calculated column in Power BI that shows the full name by combining 'FirstName' and 'LastName' columns with a space. Which DAX expression should you use?

You are modeling data from a SQL database that has a table with columns: OrderID, CustomerID, OrderDate, ProductID, Quantity, and Price. You want to create a star schema in Power BI. Which columns should you move to dimension tables?

You have a Power BI data model with a table 'Orders' related to 'Customers' (one-to-many). A measure calculates total sales per customer. Some customers have no orders, but they still appear in the report with blank sales. What should you do to hide these customers?

You are creating a calculated table in Power BI that contains a list of unique products from the 'Sales' table. Which DAX function should you use?

You have a Power BI report that shows sales by region. The data model contains a 'Sales' fact table and a 'Region' dimension table. When you filter by a specific region, the total sales for that region is correct, but the grand total shows all sales. What is the likely cause?

You need to design a data model for a sales analysis that includes measures for total sales, sales by product, and sales by customer. The source data has a 'Transactions' table with columns: TransactionID, Date, CustomerID, ProductID, Quantity, Amount. What is the recommended star schema design?

You want to create a measure that calculates the total sales for the current year. Which DAX expression should you use?

Which TWO of the following are best practices when designing a Power BI data model?

Which THREE of the following are valid reasons to create a calculated table in Power BI?

Which TWO of the following are valid DAX functions for filtering data?

You are a Power BI developer at a retail company. You have a data model with a 'Sales' fact table (10 million rows) and dimension tables: 'Date', 'Customer', 'Product', 'Store'. The 'Sales' table includes columns: SalesID, DateKey, CustomerID, ProductID, StoreID, Quantity, UnitPrice, Discount, TotalAmount. The 'Product' dimension has 5,000 rows and includes columns: ProductID, ProductName, Category, SubCategory, Brand, Price. The 'Store' dimension has 200 rows and includes columns: StoreID, StoreName, Region, City, Manager. The 'Customer' dimension has 100,000 rows. The report currently has a measure 'Total Sales' = SUM(Sales[TotalAmount]) and a measure 'Total Quantity' = SUM(Sales[Quantity]). Users complain that the report is slow when filtering by multiple categories and regions simultaneously. You need to improve performance without changing the data source. Which action should you take first?

You are building a Power BI report for a logistics company. The data source is a SQL Server database with tables: 'Shipments' (columns: ShipmentID, OrderDate, ShipDate, CustomerID, Origin, Destination, Weight, Cost, Revenue), 'Customers' (CustomerID, CustomerName, Segment, Country), and 'Calendar' (Date, Year, Month, Quarter). You need to create a star schema in Power BI. You have already created the relationships. When you try to create a measure to calculate the average delivery time (ShipDate - OrderDate), you get an error because the data types are datetime. You want to create a calculated column in the Shipments table that shows the delivery time in days. Which DAX expression should you use?

You are a Power BI analyst at a marketing agency. You have a data model with a 'Campaigns' table (columns: CampaignID, CampaignName, StartDate, EndDate, Budget, Spent) and a 'Results' table (columns: ResultID, CampaignID, Date, Impressions, Clicks, Conversions). You need to model the data to analyze campaign performance over time. You create a relationship between Campaigns and Results on CampaignID (one-to-many). You also create a date dimension 'Calendar' and relate it to Results[Date]. However, when you create a measure to calculate the total budget by month, the budget for a campaign that spans multiple months is counted in each month, leading to double-counting. What should you do to accurately allocate the budget across months?

You are building a Power BI semantic model that combines sales data from an on-premises SQL Server database and a cloud-based CRM system. The CRM system returns data in a de-normalized format with multiple fact tables. You need to design the model to minimize data duplication and improve query performance. What should you do?

You have a Power BI semantic model with a date table that spans from January 1, 2020 to December 31, 2025. You want to calculate year-to-date (YTD) sales for the current year. Which DAX formula should you use?

You are designing a Power BI semantic model for a retail company. The model includes a Sales table (50 million rows) and a Product table (10,000 rows). You need to create a measure that calculates the average sales amount per product category. The Product table has a column 'Category' with 20 distinct values. To optimize performance, what should you do?

You have a Power BI semantic model that uses row-level security (RLS). The model contains a table 'Employees' with columns: EmployeeID, ManagerID, Region. You need to configure RLS so that a manager can see only the data for employees who report to them, including indirect reports (i.e., the entire hierarchy under the manager). What is the best approach?

Which TWO actions should you take to improve the performance of a DirectQuery model in Power BI? (Select two.)

Which THREE factors should you consider when designing a star schema for a Power BI semantic model? (Select three.)

Which TWO are valid reasons to use a date table in a Power BI semantic model? (Select two.)

Refer to the exhibit. You have a Power BI semantic model with a role 'Sales Manager'. The role is defined with read permission on the Sales table but only on the Amount column. When the user 'salesmgr@contoso.com' creates a report using this model, which of the following will they be able to see?

You are a data analyst at a multinational retail company. The company uses Microsoft Power BI to analyze sales data from multiple regions. The source data is stored in Azure SQL Database and includes tables: Sales (OrderID, ProductID, Quantity, Amount, OrderDate, StoreID), Stores (StoreID, StoreName, Region, Country), Products (ProductID, ProductName, Category, Price). The model is imported daily. You need to design a semantic model that supports the following requirements: 1) Allow users to filter by year and month using a single slicer. 2) Ensure that time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) work correctly. 3) Minimize model size. 4) Provide a consistent date dimension for all fact tables. The Sales table has orders from 2018-01-01 to 2025-12-31. You decide to create a date table. Which of the following approaches should you take?

You are building a Power BI semantic model for a healthcare provider. The model must track patient visits and procedures. You have three source tables: Patients (PatientID, Name, DOB, Gender), Visits (VisitID, PatientID, VisitDate, DoctorID), Procedures (ProcedureID, VisitID, ProcedureCode, Cost). The model should allow users to analyze procedure costs by patient demographics (gender, age group) and by date (year, quarter, month). You need to design the star schema. Which of the following is the most appropriate design?

You are developing a Power BI report for a sales team. The data source is an Excel file with a single sheet containing columns: Date, Salesperson, Product, Units Sold, Revenue. The file is updated weekly. You need to model the data to allow analysis of revenue by salesperson and product over time. What is the simplest and most effective approach?

You are a Power BI developer for a financial services company. The company has a large transactional database in Azure Synapse Analytics. The database contains a table 'Transactions' with 2 billion rows. The table includes columns: TransactionID, AccountID, TransactionDate, Amount, Type (Deposit/Withdrawal), Status (Pending/Completed). You need to build a Power BI semantic model that allows executives to analyze monthly trends of completed deposit amounts by account type (e.g., Savings, Checking). The account type is in a separate 'Accounts' table (1 million rows) with columns: AccountID, AccountType, CustomerID. The model must refresh within 2 hours. Due to the large data volume, you cannot import the entire Transactions table. What should you do?

You are developing a Power BI semantic model for an e-commerce company. The source data comes from a CSV file containing order details: OrderID, OrderDate, CustomerID, ProductID, Quantity, UnitPrice, Discount, and ShippingCost. The file is updated daily. You need to model the data to support the following analyses: 1) Total sales amount (Quantity * UnitPrice - Discount) by product and month. 2) Average shipping cost per order by customer region (CustomerRegion is in a separate table). 3) Year-over-year comparison of sales. You need to create the measures and ensure optimal performance. What should you do?

You are creating a Power BI report for a small business. The data source is a Microsoft Access database with tables: Customers (CustomerID, CompanyName, City), Orders (OrderID, CustomerID, OrderDate, Amount). You need to model the data to analyze total orders by customer and by month. What is the most efficient approach?

You are a data modeler for a logistics company. The company uses Power BI to analyze shipment data. The source system is a SQL Server database with tables: Shipments (ShipmentID, ShipDate, CustomerID, Weight, Cost, CarrierID), Customers (CustomerID, CustomerName, Region), Carriers (CarrierID, CarrierName, Mode). The database is updated in real-time. You need to build a semantic model that supports near real-time reporting with maximum data freshness while maintaining good query performance. The model should allow users to filter by customer region and carrier mode, and calculate total cost and weight per month. What is the best approach?

Which TWO actions should you take to optimize a star schema in Power BI?

Which THREE considerations are important when designing a Power BI data model for large datasets?

Which TWO DAX functions can be used to implement row-level security (RLS) in Power BI?

Which THREE data types are supported in Power Query for Power BI?

Which THREE actions can improve query performance in a Power BI DirectQuery model?

You are a data analyst for a retail company. You have a Power BI semantic model that includes a fact table named Sales with columns: Date, ProductID, StoreID, Quantity, and Amount. You also have dimension tables: Product, Store, and Date. The Date table is marked as a date table. You need to create a measure that calculates the running total of sales amount over the last 12 months, including the current month. The measure should be dynamic based on the filter context. Which DAX expression should you use?

You are building a Power BI report for a multinational corporation. The data model includes a fact table named Orders with columns: OrderID, CustomerID, OrderDate, ProductID, Quantity, UnitPrice, and Discount. The Customer dimension contains columns: CustomerID, CustomerName, Country, and Segment. The Product dimension contains: ProductID, ProductName, Category, Subcategory, and Price. You need to create a calculated column in the Orders table that calculates the net amount after discount for each order line (Quantity * UnitPrice * (1 - Discount)). You also need to ensure that the column is stored in the model for high-performance filtering. Which DAX expression should you use?

You are a Power BI developer for a healthcare organization. You have a semantic model that contains a table named PatientVisits with columns: VisitID, PatientID, VisitDate, DiagnosisCode, and Charges. You have a separate table named Diagnosis with columns: DiagnosisCode, DiagnosisDescription, and Category. The Diagnosis table contains duplicate rows for the same DiagnosisCode but with different descriptions due to data entry errors. You need to create a relationship between PatientVisits and Diagnosis on DiagnosisCode. However, the duplicate values in Diagnosis prevent creating a one-to-many relationship. You must ensure that the relationship can be created without removing any rows from the Diagnosis table. What should you do?

You are a data analyst for a financial services firm. You have a Power BI semantic model that uses DirectQuery mode against a SQL Server data warehouse. The model includes a large fact table named Transactions with billions of rows. Users are complaining that the report is slow when filtering by date range. You need to improve the performance of date-related queries without changing the data source structure. You cannot switch to Import mode due to data volume constraints. What should you do?

You are a Power BI developer for an e-commerce company. You have a semantic model that contains a table named Orders with columns: OrderID, CustomerID, OrderDate, ProductID, Quantity, and SalesAmount. You also have a table named Products with columns: ProductID, ProductName, Category, and Price. You need to create a measure that calculates the percentage of total sales for each product category. The measure should be used in a matrix visual with Category on rows. Which DAX expression should you use?

You are a data analyst for a logistics company. You have a Power BI semantic model that contains a table named Shipments with columns: ShipmentID, OriginCity, DestinationCity, ShipDate, DeliveryDate, Weight, and Cost. The model also contains a table named Cities with columns: City, State, Region, and Population. You need to create a measure that calculates the average delivery time in days for shipments that originated from cities with a population greater than 1 million. The measure should be efficient. Which DAX expression should you use?

You are a Power BI report creator for a university. You have a semantic model with a table named Enrollments with columns: EnrollmentID, StudentID, CourseID, EnrollmentDate, and Grade. You also have tables: Students (StudentID, StudentName, Major) and Courses (CourseID, CourseName, Department). You need to create a measure that counts the number of students who have enrolled in at least one course in the 'Science' department. The measure should be efficient and respect any filters on the report. Which DAX expression should you use?

You are a Power BI administrator for a large enterprise. You have a Power BI semantic model that uses a single large fact table named Sales (100 million rows) and several dimension tables. The model is used by multiple departments, each with different row-level security (RLS) rules based on the SalesRegion column. You have implemented RLS using static roles. However, you notice that when users from different departments view the same report page, the query performance varies significantly. You suspect that the RLS filters are causing the performance difference. You need to investigate and optimize the RLS performance. What should you do first?