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Exam Code: C9560-519

Exam Name: IBM Tivoli Netcool/OMNIbus V8.1 Implementation

Certification Provider: IBM

Related Certification: IBM Tivoli Netcool/OMNIbus V8.1 Implementation

C9560-519 IBM Tivoli Netcool/OMNIbus V8.1 Implementation

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Which of the following is BEST used to capture and analyze network traffic between hosts on the same network segment?
A. Router
C. Firewall
D. Protocol analyzer
Answer: D
A Protocol Analyzer is a hardware device or more commonly a software program used to capture network data communications sent between devices on a network. Capturing and analyzing the packets sent from two systems that are not communicating properly could help determine the cause of the issue.
Well known software protocol analyzers include Message Analyzer (formerly Network Monitor) from Microsoft and Wireshark (formerly Ethereal).

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.



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: models-olap-logical-cube-objects/partitions-partition-storage-modes-and-processing
Topic 3, Case Study #3
You are a developer for a Seattle-based company. The company is expanding globally.
Many company employees speak fluent Mandarin and read Simplified Chinese.
You have six tabular data models that are deployed to two instances of Microsoft SQL
Server Analysis Services (SSAS).
Users report that the query takes a long time to complete.
You are planning the disk space allocations for a new Microsoft SQL Server Analysis
Services deployment. You plan to move several relational data file databases to the new
SSAS instance. The databases require a total of 10 GB of disk space.
You also plan to deploy Cubes and Aggregations and use Object Processing. Cubes will have small fact tables and few dimension members. No unnecessary aggregations will be created. You plan to process an entire cube in a single transaction.
Data Models
One of the data models is named CustomerSales. This data model contains eight tables.
The model includes a table named Sales that defines several measures, including a measure named PriorYearSales. The PriorYearSales measure is referenced by other measures, and is not intended to be analyzed directly by users. You must translate the metadata for all fata the CustomerSales data model to Simplifies Chinese. Team members from the Shanghai office assist with identifying appropriate translations.
A data model named OrderAnalysis is deployed to one of the SSAS instances. Order data is loaded into the OrderAnalysis data as part of an overnight process. You observe that the model is not up-to-date.
The business analysis team uses a variety of client applications to issue MDX queries against OrderAnalysis. Order data must be completely up-to-date.
The OrderAnalysis model has two user-defined hierarchies that are defined in a table named Order. New customers are only added once per day. The overnight process is sufficiently up-to-date for the Customer data to provide optimal performance while achieving the data currency goals whenever possible.
You deploy a database named DB1 to an SSAS instance as a project by using SQL Server
Data Tools. Data analysts report that they cannot access near real time data from the
SSAS SalesAnalysis model from DB1. You discover that the project has been deployed with the Direct Query Mode option set to OFF.
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.

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