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NEW QUESTION 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. Process the model in Process Full mode.
- B. Ensure that DirectQuery is disabled for the model.
- C. Process the model in Process Data mode.
- D. Process the model in Process Defrag mode.
- E. Ensure that the Transactional Deployment property is set to False.
- F. Ensure that DirectQuery is enabled for the model.
- G. Ensure that the Transactional Deployment property is set to True.
Answer: F
Explanation:
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/
NEW QUESTION 21
DRAG DROP
You are writing a MDX query to retrieve data from a Microsoft SQL Server Analysis
Services (SSAS) cube named Channel Sales. The cube defines two measures named
Sales and Cost. The cube also defines a Date dimension and a Product dimension.
You need to retrieve profit values for a year named CY2016.
How should you complete the MDX statement? To answer, drag the appropriate MDX segment to the correct locations. Each MDX segment 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:
Explanation:
Box 1:WITH MEMBER...
Box 2:WHERE ([Date].[Year].[CY2016])
References: https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional- models/mdx/working-with-members-tuples-and-sets-mdx
NEW QUESTION 22
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:
Users need to be able to analyze sales by product and color.
You need to create the dimension.
Which relationship type should you use between the InternetSales table and the new dimension?
- A. regular
- B. data mining
- C. many-to-many
- D. fact
- E. no relationship
- F. referenced
Answer: F
Explanation:
A reference dimension relationship between a cube dimension and a measure group exists when the key column for the dimension is joined indirectly to the fact table through a key in another dimension table, as shown in the following illustration.
A reference dimension relationship represents the relationship between dimension tables and a fact table in a snowflake schema design. When dimension tables are connected in a snowflake schema, you can define a single dimension using columns from multiple tables, or you can define separate dimensions based on the separate dimension tables and then define a link between them using the reference dimension relationship setting. The following figure shows one fact table named InternetSales, and two dimension tables called
Customer and Geography, in a snowflake schema.
You can create two dimensions related to the InternetSales measure group: a dimension based on the Customer table, and a dimension based on the Geography table. You can then relate the Geography dimension to the InternetSales measure group using a reference dimension relationship using the Customer dimension.
NEW QUESTION 23
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. No
- B. Yes
Answer: A
Explanation:
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 24
DRAG DROP
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:
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.
NEW QUESTION 25
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:
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. regular
- B. referenced
- C. data mining
- D. many-to-many
- E. fact
- F. no relationship
Answer: A
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.
https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models-olap-logical- cube-objects/dimension-relationships
NEW QUESTION 26
You are managing a SQL Server Analysis Services (SSAS) tabular database.
The database must meet the following requirements:
*
The processing must load data into partitions or tables.
*
The processing must not rebuild hierarchies or relationships.
*
The processing must not recalculate calculated columns.
You need to implement a processing strategy for the database to meet the requirements.
Which processing mode should you use?
- A. Process Default
- B. Process Data
- C. Process Add
- D. Process Clear
- E. Process Full
Answer: C
NEW QUESTION 27
Drag and Drop Question
A database named DB2 uses the InMemory query mode. Users frequently run the following query:
You need to reconfigure the SSAS instance that hosts DB1.
Which three actions should 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:
Explanation:
Step 1: Set the default mode for the data model to DirectQuery. You discover that the project has been deployed with the Direct Query Mode option set to OFF.
Step 2: Set the mode for the FactInternetSales table's partition to DirectQueryOnly. Initially, even DirectQuery models are always created in memory. The default query mode for the workspace database is also set toDirectQuery with In-Memory. This hybrid working mode lets you use the cache of imported data for improved performance during the model design process, while validating the model against DirectQuery requirements.
From Scenario: Most queries that use the SalesAnalysis data model use data from a table named FactInternetSales that is 20 gigabyte (GB) in size. Cached data must be available for the FactInternetSales table. All queries accessing the SalesAnalysis model must be executed in near real time.
Step 3: Run Process Full for the FactInternetSales partition. 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
NEW QUESTION 28
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: Change the storage mode for the data model to DirectQuery.
Does the solution meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
Explanation/Reference:
Explanation:
By default, tabular models use an in-memory cache to store and query data. When tabular models query data residing in-memory, even complex queries can be incredibly fast. However, there are some limitations to using cached data. Namely, large data sets can exceed available memory, and data freshness requirements can be difficult if not impossible to achieve on a regular processing schedule.
DirectQuery overcomes these limitations while also leveraging RDBMS features making query execution more efficient.
With DirectQuery: +
Data is up-to-date, and there is no extra management overhead of having to maintain a separate copy of the data (in the in-memory cache). Changes to the underlying source data can be immediately reflected in queries against the data model.
Datasets can be larger than the memory capacity of an Analysis Services server.
Etc.
References:https://docs.microsoft.com/en-us/sql/analysis-services/tabular-models/directquery-mode-ssas- tabular
NEW QUESTION 29
HOTSPOT
You have a Microsoft SQL Server Analysis Services (SSAS) multidimensional project. You are developing a dimension that uses data from the following table:
The ManagerKey column defines a foreign key constraint that references the EmployeeKey column. The table stores employee history information by using slowly changing dimensions (SCD). Changes to EmployeeName, Phone, or ManagerKey are managed as
SCD Type 1 changes. Changes to SalesRegion are managed as SCD Type 2 changes.
You create the following attributes, and set the KeyColumns and NameColumn properties to the columns listed in the table below:
You need to add a parent-child hierarchy to the dimension to enable navigating the organization hierarchy.
In the table below, identify the attribute that you must use for each attribute usage type.
NOTE: Make only one selection in each column.
Answer:
Explanation:
Explanation:
The ManagerKey column, the Manager attribute, defines a foreign key constraint that references the EmployeeKey column, the Employee attribute.
NEW QUESTION 30
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?
Answer:
Explanation:
The following example returns the sum of the Measures. [Order Quantity] member, aggregated over the first eight months of calendar year 2003 that are contained in the Date dimension, from the Adventure Works cube.
Copy
WITH MEMBER [Date].[Calendar].[First8Months2003] AS
Aggregate(
PeriodsToDate(
[Date].[Calendar].[Calendar Year],
[Date].[Calendar].[Month].[August 2003]
)
)
SELECT
[Date].[Calendar].[First8Months2003] ON COLUMNS,
[Product].[Category].Children ON ROWS
FROM
[Adventure Works]
WHERE
[Measures].[Order Quantity]
References: https://docs.microsoft.com/en-us/sql/mdx/aggregate-mdx
NEW QUESTION 31
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. No
- B. Yes
Answer: A
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 32
HOTSPOT
A database named DB2 uses the InMemory query mode. Users frequently run the following query:
You need to configure SQL Server Profiler to determine why the query is performing poorly.
Which three event should you monitor on the SQL Server Profiler trace events configuration page? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation:
By using SQL Profiler, you can intercept two classes of trace events from Analysis Services, DAX Query Plan and DirectQuery events, both generated by the DirectQuery engine. Here, in this scenario we have a DAX Query.
DAX Query Plan events are generated by the DAX formula.
By using the In-Memory mode, you store a copy of data in the xVelocity (VertiPaq) storage engine.
Figure: This is how a query is executed by using In-Memory mode.
References: Microsoft SQL Server 2012 Analysis Services, The BISM Tabular Model, Microsoft Press (July 2012), page 331 From Scenario: Users report that the query takes a long time to complete.
NEW QUESTION 33
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. Process the model in Process Full mode.
- B. Ensure that DirectQuery is disabled for the model.
- C. Process the model in Process Data mode.
- D. Ensure that the Transactional Deployment property is set to True.
- E. Ensure that DirectQuery is enabled for the model.
- F. Process the model in Process Defrag mode.
- G. Ensure that the Transactional Deployment property is set to False.
Answer: D
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.
https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models/deployment- script-files-specifying-processing-options
NEW QUESTION 34
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?
- A. Install two separate tabular instances of SSAS.
- B. Install one tabular instance of SSAS and enable the Data Mining Extensions.
- C. Install a multidimensional instance and a Power Pivot instance of SSAS on the same server.
- D. Install one tabular instance of SSAS.
- E. Install one multidimensional instance of SSAS.
Answer: D,E
NEW QUESTION 35
DRAG DROP
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:
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.
===============================================
Topic 1, Wide World Importers
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.
NEW QUESTION 36
You are developing a SQL Server Analysis Services (SSAS) cube.
The data warehouse has a table named FactStock that is used to track movements of stock.
A column named MovementQuantity contains quantities of stock.
A positive quantity is used for input and negative quantity is used for output.
A column named MovementDate is related to the time dimension.
The quantity in stock, at a given point in time, can be evaluated as the sum of all MovementQuantity values at that point in time.
You need to create a measure that calculates the quantity in stock value.
What should you do?
- A. Create several dimensions. Add each dimension to the cube.
- B. Add a measure that uses the DistinctCount aggregate function to an existing measure group.
- C. Create a dimension. Create regular relationships between the cube dimension and the measure group. Configure the relationships to use different dimension attributes.
- D. Add a measure that uses the Count aggregate function to an existing measure group.
Answer: D
NEW QUESTION 37
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. No
- B. Yes
Answer: A
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION 38
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.
Answer:
Explanation:
Explanation:
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 39
DRAG DROP
You are a business analyst for a company that uses a Microsoft SQL Server Analysis
Services (SSAS) tabular database for reporting. The database model contains the following tables:
You have been asked to write a query for a report that returns the total sales for each product subcategory, as well as for each product category.
You need to write the query to return the data for the report.
How should you complete the DAX statement? To answer, drag the appropriate DAX segment to the correct locations. Each DAX segment 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:
Explanation:
Box 1:EVALUATE
Box 2:SUMMERIZE
Box 3:ROLLUP
Box 4:'Product Subcategory' ['Product Subcategory Name]
Note: The behavior of SUMMARIZE is similar to the GROUP BY syntax of a SELECT statement in SQL. For example, consider the following query.
EVALUATE
SUMMARIZE(
'Internet Sales',
'Internet Sales'[Order Date],
"Sales Amount", SUM( 'Internet Sales'[Sales Amount] )
)
This query calculates the total of Sales Amount for each date in which there is at least one order,
producing this result.
References:
NEW QUESTION 40
......
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