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.
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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.

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

Using perspectives in the data model might help you expose a subset of tables, columns, and measures that are useful for a particular type of analysis.
Usually, every user needs only a subset of data you create, and showing him or her the model through perspectives can offer a better user experience.
From scenario; The PriorYearSales measure is referenced by other measures, and is not intended to be analyzed directly by users.
References: Microsoft SQL Server 2012 Analysis Services, The BISM Tabular Model,
Microsoft Press (July 2012), page 305
Topic 4, Mix Questions

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