Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You have an existing multidimensional cube that provides sales analysis. The users can slice by date, product, location, customer, and employee.
The management team plans to evaluate sales employee performance relative to sales targets. You identify the following metrics for employees:
You need to implement the KPI based on the Status expression.
Solution: You design the following solution:

Does the solution meet the goal?

DRAG DROP
Case Study #2
This is a case study. Case studies are not limited separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
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Background
Wide World Importers has multidimensional cubes named SalesAnalysis and ProductSales. The SalesAnalysis cube is refreshed from a relational data warehouse. You have a Microsoft SQL Server Analysis Services instance that is configured to use tabular mode. You have a tabular data model named CustomerAnalysis.
Sales Analysis
The SalesAnalysis cube contains a fact table named CoffeeSale loaded from a table named FactSale in the data warehouse. The time granularity within the cube is 15 minutes. The cube is processed every night at 23:00. You determine that the fact table cannot be fully processed in the expected time. Users have reported slow query response times.
The SalesAnalysis model contains tables from a SQL Server database named SalesDB. You set the DirectQueryMode option to DirectQuery. Data analyst access data from a cache that is up to 24 hours old.
Data analyst report performance issues when they access the SalesAnalysis model.
When analyzing sales by customer, the total of all sales is shown for every customer, instead of the customer's sales value. When analyzing sales by product, the correct totals for each product are shown.
Customer Analysis
You are redesigning the CustomerAnalysis tabular data model that will be used to analyze customer sales.
You plan to add a table named CustomerPermission to the model. This table maps the Active Directory login of an employee with the CustomerId keys for all customers that the employee manages.
The CustomerAnalysis data model will contain a large amount of data and needs to be shared with other developers even if a deployment fails. Each time you deploy a change during development, processing takes a long time.
Data analysts must be able to analyze sales for financial years, financial quarters, months, and days. Many reports are based on analyzing sales by month.
Product Sales
The ProductSales cube allows data analysts to view sales information by product, city, and time. Data analysts must be able to view ProductSales data by Year to Date (YTD) as a measure. The measure must be formatted as currency, associated with the Sales measure group, and contained in a folder named Calculations.
Requirements
You identify the following requirements:
Data available during normal business hours must always be up-to-date.

Processing overhead must be minimized.

Query response times must improve.

All queries that access the SalesAnalysis model must use cached data by default.

Data analysts must be able to access data in near real time.

You need to configure the CoffeeSale fact table environment.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Select and Place:

Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You administer a Microsoft SQL Server Analysis Services (SSAS) tabular model for a retail company. The model is the basis for reports on inventory levels, popular products, and regional store performance.
The company recently split up into multiple companies based on product lines. Each company starts with a copy of the database and tabular model that contains data for a specific product line.
You need to optimize performance of queries that use the copied tabular models while minimizing downtime.
What should you do?

HOTSPOT
You are deploying a multidimensional Microsoft SQL Server Analysis Services (SSAS) project. You add two new role-playing dimensions named Picker and Salesperson to the cube. Both of the cube dimensions are based upon the underlying dimension named Employee in the data source view.
Users report that they are unable to differentiate the Salesperson attributes from the Picker attributes.
You need to ensure that the Salesperson and Picker attributes in each dimension use unique names.
In the table below, identify an option that you would use as part of the process to alter the names of the attributes for each of the dimensions.
NOTE: Make only one selection in each column.

You are optimizing a Microsoft SQL Server Analysis Services (SSAS) multidimensional model over a SQL Server database.
You have a table named City which has several dimensions that do not contain a space in their names.
One dimension is named SalesTerritory rather than Sales Territory.
You need to ensure that Report developers can drag the attribute name to the report rather than having to re-label the attributes by implementing spaces.
You must minimize administrative effort and not break any upstream processes.
What should you do?