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Developing SQL Data Models

Question No: 11 – (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 travel agency that specializes in vacation packages. Vacation bookings and packages are stored in a SQL Server database. You use the model as the basis for customer emails that highlight vacation packages that are currently underbooked, or projected to be underbooked.

The company plans to incorporate cruise ship vacation packages. Cruise ship vacation packages include new features such as region availability and cruise line specialties that require changes to the tabular model.

You must ensure that the tabular model reflects the new vacation packages. You need to configure the tabular data model.

What should you do?

  1. Ensure that DirectQuery is enabled for the model.

  2. Ensure that DirectQuery is disabled for the model.

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

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

  5. Process the model in Process Full mode.

  6. Process the model in Process Data mode.

  7. Process the model in Process Defrag mode.

Answer: E Explanation:

Process Full processes an Analysis Services object and all the objects that it contains. 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.

Question No: 12 – (Topic 4)

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:

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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.):

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

A.

B.

C.

D.

Answer: B 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

Question No: 13 – (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 are developing Microsoft SQL Server Analysis Services (SSAS) tabular model.

The model must meet the following requirements: You need to configure model.

What should you do?

  1. Ensure that DirectQuery is enabled for the model.

  2. Ensure that DirectQuery is disabled for the model.

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

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

  5. Process the model in Process Full mode.

  6. Process the model in Process Data mode.

  7. Process the model in Process Defrag mode.

Answer: A 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/

Question No: 14 – (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?

  1. Ensure that DirectQuery is enabled for the model.

  2. Ensure that DirectQuery is disabled for the model.

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

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

  5. Process the model in Process Full mode.

  6. Process the model in Process Data mode.

  7. 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

Question No: 15 – (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:

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Does the solution meet the goal?

  1. Yes

  2. No

Answer: B

Question No: 16 – (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 have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:

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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?

  1. no relationship

  2. regular

  3. fact

  4. referenced

  5. many-to-many

  6. 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

Question No: 17 – (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: Install solid-state disk drives to store the tabular data model. Does the solution meet the goal?

  1. Yes

  2. No

Answer: B 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:

References:https://docs.microsoft.com/en-us/sql/analysis-services/tabular- models/directquery-mode-ssas-tabular

Question No: 18 – (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: Change the storage mode for the data model to DirectQuery. Does the solution meet the goal?

  1. Yes

  2. No

Answer: A 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

Question No: 19 – (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 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:

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

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You need to create the KPI.

Solution: You set the value of the Status expression to:

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Does the solution meet the goal?

  1. Yes

  2. No

Answer: A

Question No: 20 – (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 have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:

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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?

  1. no relationship

  2. regular

  3. fact

  4. referenced

  5. many-to-many

  6. data mining

Answer: E 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.

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

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