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 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 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 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 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 TWO 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?

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

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 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 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 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 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 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?

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

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 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 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?

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

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 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 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?

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

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 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?

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

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 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 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?

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

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 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?

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

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

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 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 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 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?

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

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

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

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 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?

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

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 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?