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NEW QUESTION NO: 10
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.
A company has an e-commerce website. When a customer places an order, information about the transaction is inserted into tables in a Microsoft SQL Server relational database named OLTP1. The company has a SQL Server Analysis Services (SSAS) instance that is configured to use Tabular mode.
SSAS uses data from OLTP1 to populate a data model.
Sales analysts build reports based on the SSAS model. Reports must be able to access data as soon as it is available in the relational database.
You need to configure and deploy an Analysis Services project to the Analysis Services instance that allows near real-time data source access.
Solution: In the Deployment Option property for the report, you set the Query Mode to InMemory.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation/Reference:
Explanation:
With InMemory the queries can use the cache only.
References:https://msdn.microsoft.com/en-us/library/hh230898(v=sql.120).aspx

NEW QUESTION NO: 11
You are responsible for installing new database server instances.
You must install Microsoft SQL Server Analysis Services (SSAS) to support deployment of the following projects. You develop both projects by using SQL Server Data Tools.
Project1 uses the tabular data model.

Project2 uses SQL Server data mining to predict customer-purchasing intentions by using the Decision

Trees algorithm.
You need to install the appropriate services to support both projects.
Which two actions should you perform? Each correct answer presents part of the solution.
A. Install one tabular instance of SSAS and enable the Data Mining Extensions.
B. Install one multidimensional instance of SSAS.
C. Install one tabular instance of SSAS.
D. Install a multidimensional instance and a Power Pivot instance of SSAS on the same server.
E. Install two separate tabular instances of SSAS.
Answer: B,C
Explanation/Reference:
Explanation:
Analysis Services can be installed in one of three server modes: Multidimensional and Data Mining (default), Power Pivot for SharePoint, and Tabular.
References:https://docs.microsoft.com/en-us/sql/analysis-services/comparing-tabular-and- multidimensional-solutions-ssas

NEW QUESTION NO: 12
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.
A company has an e-commerce website. When a customer places an order, information about the transaction is inserted into tables in a Microsoft SQL Server relational database named OLTP1. The company has a SQL Server Analysis Services (SSAS) instance that is configured to use Tabular mode.
SSAS uses data from OLTP1 to populate a data model.
Sales analysts build reports based on the SSAS model. Reports must be able to access data as soon as it is available in the relational database.
You need to configure and deploy an Analysis Services project to the Analysis Services instance that allows near real-time data source access.
Solution: In the Deployment Option property for the report, you set the Query Mode to InMemory with DirectQuery.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation/Reference:
Explanation:
With InMemory with DirectQuery: Queries use the cache by default, unless otherwise specified in the connection string from the client.
References: https://msdn.microsoft.com/en-us/library/hh230898(v=sql.120).aspx

NEW QUESTION NO: 13
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?
A. Yes
B. No
Answer: B
Explanation/Reference:
Explanation:

NEW QUESTION NO: 14
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?
A. In the SQL Server database, run the system procedure sp_rename to rename the columns in the base tables with the target name.
B. In SQL Server Management Studio, navigate to the City table, expand the columns, press F2, and rename the columns in the base tables.
C. In the SQL Server database, implement a SYNONYM.
D. In the SQL Server database, implement a view over the City table that aliases the columns in the tables.
Answer: D
Explanation/Reference:
Explanation:

NEW QUESTION NO: 15
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.
Hot Area:

Answer: 

Explanation/Reference:
A named query is a SQL expression represented as a table. In a named query, you can specify an SQL expression to select rows and columns returned from one or more tables in one or more data sources. A named query is like any other table in a data source view (DSV) with rows and relationships, except that the named query is based on an expression.
A named query lets you extend the relational schema of existing tables in DSV without modifying the underlying data source.
References: https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models/define- named-queries-in-a-data-source-view-analysis-services

NEW QUESTION NO: 16
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.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other question on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next sections of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
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 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.
Select and Place:

Answer: 

Explanation/Reference:
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.

NEW QUESTION NO: 17
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 have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:

You need to create a new dimension that allows users to list shipments by the country where the product is shipped.
Which relationship type should you use between the Shipment table and the new dimension?
A. no relationship
B. regular
C. fact
D. referenced
E. many-to-many
F. data mining
Answer: E
Explanation/Reference:
Explanation:
Many to Many Dimension Relationships.
In most dimensions, each fact joins to one and only one dimension member, and a single dimension member can be associated with multiple facts. In relational database terminology, this is referred to as a one-to-many relationship. However, it is frequently useful to join a single fact to multiple dimension members. For example, a bank customer might have multiple accounts (checking, saving, credit card, and investment accounts), and an account can also have joint or multiple owners. The Customer dimension constructed from such relationships would then have multiple members that relate to a single account transaction.

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

NEW QUESTION NO: 18
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:
Ninety percent or greater relative to sales target values is considered on target.

Between 75 percent and 90 percent is considered slightly off target.

Below 75 percent is considered off target.

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
Explanation/Reference:
Explanation:

NEW QUESTION NO: 19
Case Study #1
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.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other question on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next sections of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Background
Wide World Importers imports and sells clothing. The company has a multidimensional Microsoft SQL Server Analysis Services instance. The server has 80 gigabytes (GB) of available physical memory. The following installed services are running on the server:
SQL Server Database Engine
SQL Server Analysis Services (multidimensional)
The database engine instance has been configured for a hard cap of 50 GB, and it cannot be lowered. The instance contains the following cubes: SalesAnalysis, OrderAnalysis.
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.
Processing for all cubes must occur automatically in increments. You create one job to process the cubes and another job to process the dimensions. You must configure a processing task for each job that optimizes performance. As the cubes grown in size, the overnight processing of the cubes often do not complete during the allowed maintenance time window.
SalesAnalysis
The SalesAnalysis cube is currently being tested before being used in production. Users report that day name attribute values are sorted alphabetically. Day name attribute values must be sorted chronologically.
Users report that they are unable to query the cube while any cube processing operations are in progress.
You need to maximize data availability during cube processing and ensure that you process both dimensions and measures.
OrderAnalysis
The OrderAnalysis cube is used for reporting and ad-hoc queries from Microsoft Excel. The data warehouse team adds a new table named Fact.Transaction to the cube. The Fact.Transaction table includes a column named Total Including Tax. You must add a new measure named Transactions - Total Including Tax to the cube. The measure must be calculated as the sum of the Total Including Tax column across any selected relevant dimensions.
Finance
The Finance cube is used to analyze General Ledger entries for the company.
Requirements
You must minimize the time that it takes to process cubes while meeting the following requirements:
The Sales cube requires overnight processing of dimensions, cubes, measure groups, and partitions.

The OrderAnalysis cube requires overnight processing of dimensions only.

The Finance cube requires overnight processing of dimensions only.

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/Reference:
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.
Incorrect Answers:
B: VertiPaqPagingPolicy: For tabular instances, a lower threshold at which the server first begins releasing memory allocated to infrequently used objects.
Scenario: SQL Server Analysis Services (multidimensional) is used.
C: TotalMemoryLimit: An upper threshold at which Analysis Services begins releasing memory more aggressively to make room for requests that are in execution as well as new high priority requests.
Scenario: The database engine instance has been configured for a hard cap of 50 GB, and it cannot be lowered.
References: https://docs.microsoft.com/en-us/sql/analysis-services/server-properties/memory-properties

NEW QUESTION NO: 20
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 are developing Microsoft SQL Server Analysis Services (SSAS) tabular model.
The model must meet the following requirements:
Support the RELATED and TRUNC DAX functions.

Show updated data as quickly as possible.

You need to configure model.
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: A
Explanation/Reference:
Explanation:
DAX originally emerged from a Power Pivot add-in for Excel, as a formula language extension for creating calculated columns and measures for data analysis (which are also integral elements of one SSAS Tabular model database, too), but when Microsoft added support for DAX queries in SQL Server 2012, BI experts started "daxing" data from Tabular model databases.
That trend continues, because of simplicity and fast query execution (related to DirectQuery mode in SSAS Tabular).
References:https://www.sqlshack.com/query-ssas-tabular-model-database-using-dax-functions/