[2021-New] Microsoft 70-768 Dumps With Update Exam Questions (1-10)

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Q1. - (Topic 4)

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?

A. Ensure that DirectQuery is enabled for the model.

B. Ensure that DirectQuery is disabled for the model.

C. Ensure that the Transactional Deployment property is set to True.

D. Ensure that the Transactional Deployment property is set to False.

E. Process the model in Process Full mode.

F. Process the model in Process Data mode.

G. Process the model in Process Defrag mode.

Answer: C

Explanation:

The Transactional Deployment setting controls whether the deployment of metadata changes and process commands occurs in a single transaction or in separate transactions. If this option is True (default), Analysis Services deploys all metadata changes and all process commands within a single transaction.

If this option is False, Analysis Services deploys the metadata changes in a single transaction, and deploys each processing command in its own transaction.

References:https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models/deployment-script-files-specifying-processing-options

Q2. DRAG DROP - (Topic 1)

You need to create the cube processing job and the dimension processing job.

Which processing task should you use for each job? To answer, drag the appropriate processing tasks to the correct locations. Each processing task may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Answer:

Explanation:

Box 1: ProcessData

Processes data only without building aggregations or indexes. If there is data is in the partitions, it will be dropped before re-populating the partition with source data.

Box 2: Process Update

Forces a re-read of data and an update of dimension attributes. Flexible aggregations and indexes on related partitions will be dropped.

References:https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models/processing-options-and-settings-analysis-services

Topic 2, Case Study #2

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.

Q3. - (Topic 4)

You have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:

Users need to be able to analyze sales by color.

You need to create a dimension that contains all of the colors for products sold by the company.

Which relationship type should you use between the InternetSales table and the new dimension?

A. no relationship

B. regular

C. fact

D. referenced

E. many-to-many

F. data mining

Answer: B

Explanation:

A regular dimension relationship between a cube dimension and a measure group exists when the key column for the dimension is joined directly to the fact table.

References: https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models-olap-logical-cube-objects/dimension-relationships

Q4. - (Topic 4)

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?

A. Yes

B. No

Answer: A

Q5. - (Topic 4)

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?

A. Yes

B. No

Answer: B

Q6. DRAG DROP - (Topic 2)

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.

Answer:

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.

Q7. DRAG DROP - (Topic 1)

You need to resolve the issues that the users report.

Which processing options should you use? To answer, drag the appropriate processing option to the correct location or locations. Each processing option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Answer:

Explanation:

Box1: Process Full:

When Process Full is executed against an object that has already been processed, Analysis Services drops all data in the object, and then processes the object. This kind of processing is required when a structural change has been made to an object, for example, when an attribute hierarchy is added, deleted, or renamed.

Box 2: Process Default

Detects the process state of database objects, and performs processing necessary to deliver unprocessed or partially processed objects to a fully processed state. If you change a data binding, Process Default will do a Process Full on the affected object.

Box 3:

Not Process Update: Forces a re-read of data and an update of dimension attributes. Flexible aggregations and indexes on related partitions will be dropped.

Q8. - (Topic 4)

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?

A. Yes

B. No

Answer: B

Explanation:

In this scenario we would need both Buffer Cache Extensions and SSD.

The buffer pool extension provides the seamless integration of a nonvolatile random access memory (that is, solid-state drive) extension to the Database Engine buffer pool to

significantly improve I/O throughput.

References:https://docs.microsoft.com/en-us/sql/database-engine/configure-windows/buffer-pool-extension

Q9. DRAG DROP - (Topic 2)

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.

Answer:

Explanation:

Step 1: Partition the CoffeSale facto table.

Step 2: Set the storage mode for all partitions to HOLAP.

Partitions stored as HOLAP are smaller than the equivalent MOLAP partitions because they do not contain source data and respond faster than ROLAP partitions for queries involving summary data.

Step 3: Alter the processing job to ensure that it rearranges the partition structure each evening.

Step 4: Test that the cube meets the functional requirement for data currency and query performance.

From scenario:

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.

References:https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models-olap-logical-cube-objects/partitions-partition-storage-modes-and-processing

Q10. - (Topic 1)

You need to configure the server to optimize the afternoon report generation based on the OrderAnalysis cube.

Which property should you configure?

A. LowMemoryLimit

B. VertiPaqPagingPolicy

C. TotalMemoryLimit

D. VirtualMemoryLimit

Answer: A

Explanation:

LowMemoryLimit: For multidimensional instances, a lower threshold at which the server first begins releasing memory allocated to infrequently used objects.

From scenario: Reports that are generated based on data from the OrderAnalysis cube take more time to complete when they are generated in the afternoon each day. You examine the server and observe that it is under significant memory pressure.