70-768 Exam
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Q1. DRAG DROP - (Topic 3)
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:
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
Q2. 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.
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.
References:https://docs.microsoft.com/en-us/sql/analysis-services/multidimensional-models-olap-logical-cube-objects/partitions-partition-storage-modes-and-processing
Q3. - (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:
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. no relationship
B. regular
C. fact
D. referenced
E. many-to-many
F. data mining
Answer: D
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.
Q4. DRAG DROP - (Topic 3)
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:
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
Q5. 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.
Q6. - (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?
A. Yes
B. 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
Q7. - (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
Q8. 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.
Q9. HOTSPOT - (Topic 4)
You are a database administrator in a company that uses Microsoft SharePoint Server for all intranet sites. You are responsible for the installation of new database server instances.
You must install Microsoft SQL Server Analysis Server (SSAS) to support deployment of the following projects. You develop both projects by using SQL Server Data Tools.
You need to install the appropriate services to support both projects.
What should you do? In the table below, select the appropriate services for each project. NOTE: Make only one selection in each column. Each correct selection is worth one point.
Answer:
Explanation:
Project1:
Project2: Multidimensional
Note: Analysis Services can be installed in one of three server modes: Multidimensional and Data Mining (default), Power Pivot for SharePoint, and Tabular.
Q10. - (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