070-768 無料問題集「Microsoft Developing SQL Data Models」

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 a Microsoft SQL Server Analysis Services (SSAS) multidimensional database that stores customer and order data for customers in the United States only. The database contains the following objects:

You must create a KPI named Large Sales Target that uses the Traffic Light indicator to display status. The KPI must contain:

You need to create the KPI.
Solution: You set the value of the Status expression to:

Does the solution meet the goal?

Drag and Drop Question
You need to configure the SalesAnalysis cube to correct the sales analysis by customer calculation.
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.
正解:

Explanation:
Step 1: Open the cube editor, and open the Dimension Usage tab.
Step 2: Configure a relationship between the Customer dimension and the Sales measure group.
Use Day as the granularity.
From scenario: 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.
Step 3: Reprocess the cube.
Step 4: Deploy the project changes.
Topic 1, 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 are creating a SQL Server Analysis Services (SSAS) cube.
You need to create a time dimension. It must be linked to a measure group named Sales at the day granularity level.
It must also be linked to a measure group named Salary at the month granularity level.
What should you do?

You are developing a SQL Server Analysis Services (SSAS) tabular project.
In the data warehouse, a table named Sales Persons and Territories defines a relationship between a salesperson's name, logon ID, and assigned sales territory.
You need to ensure that each salesperson has access to data from only the sales territory assigned to that salesperson. You need to use the least amount of development effort to achieve this goal.
What should you do? (More than one answer choice may achieve the goal. Select the BEST answer.)

You are a business analyst for a retail company that uses a Microsoft SQL Server Analysis Services (SSAS) multidimensional database for reporting.
The database contains the following objects:

You must create a report that shows, for each month, the Internet sales for that month and the total Internet sales for the calendar year up to and including the current month.
You create the following MDX statement (Line numbers are included for reference only.):

You need to complete the MDX statement to return data for the report.
Which MDX segment should you use in line 01?

解説: (JPNTest メンバーにのみ表示されます)
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?

解説: (JPNTest メンバーにのみ表示されます)
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 deploy a tabular data model to an instance of Microsoft SQL Server Analysis Services (SSAS). The model uses an in-memory cache to store and query data.
The data set is already the same size as the available RAM on the server. Data volumes are likely to continue to increase rapidly.
Your data model contains multiple calculated tables.
The data model must begin processing each day at 2:00 and processing should be complete by
4:00 the same day.
You observe that the data processing operation often does not complete before 7:00. This is adversely affecting team members.
You need to improve the performance.
Solution: Enable Buffer Cache Extensions.
Does the solution meet the goal?

解説: (JPNTest メンバーにのみ表示されます)

弊社を連絡する

我々は12時間以内ですべてのお問い合わせを答えます。

オンラインサポート時間:( UTC+9 ) 9:00-24:00
月曜日から土曜日まで

サポート:現在連絡