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Category: 70-768 (v.1)

Briefing 70-768: Developing SQL Data Models (update January 16th, 2018)

Does the solution meet the goal?

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 DirectQuery with
InMemory.
Does the solution meet the goal? specified in the connection string from the client.

Does the solution meet the goal?

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?

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

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?

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

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?

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

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?

Does the solution meet the goal?

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? solid-state drive) extension to the Database Engine buffer pool to significantly improve I/O throughput.

Does the solution meet the goal?

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? 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. efficient.

Does the solution meet the goal?

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? 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. efficient. data (in the in-memory cache). Changes to the underlying source data can be immediately reflected in queries against the data model.


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