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NEW QUESTION: 1
Which type of domains is interconnected using Multicast Source Discovery Protocol?
A. PIM-SM
B. PIM-DM
C. PIM-SSM
D. DVMRP
Answer: A
Explanation:
Multicast Source Discovery Protocol (MSDP) is a Protocol Independent Multicast (PIM) family multicast routing protocol defined by Experimental RFC 3618. MSDP interconnects multiple IPv4 PIM Sparse-Mode (PIM-SM) domains which enables PIM-SM to have Rendezvous Point (RP) redundancy and inter-domain multicasting.
Reference http://en.wikipedia.org/wiki/Multicast_Source_Discovery_Protocol

NEW QUESTION: 2
Which of the following corporate actions is subject to shareholder approval?
A. Declaration of cash dividends.
B. Removal of officers.
C. Removal of directors.
D. Election of officers.
Answer: C
Explanation:
Choice "d" is correct. Shareholders have the right to elect and remove directors through the voting
process.
Choice "a" is incorrect. Officers are selected by the directors rather than by the shareholders.
Choice "b" is incorrect. Because officers are selected by the directors, generally they may be removed
only by the directors.
Choice "c" is incorrect. Dividends generally can be declared only by the directors; shareholders usually do
not have any right to declare or vote on a distribution.

NEW QUESTION: 3
DRAG DROP
Case Study #2
This is a case study. Case studies are not limited separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other question on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next sections of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
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.

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.
Select and Place:

Answer:
Explanation:

Explanation/Reference:
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

NEW QUESTION: 4
You are planning for fracture granularity.
What granularity should you use to track updates to a 1 TB clone source LUN?
A. 64 KB
B. 256 KB
C. 128 KB
D. 512 KB
Answer: A