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Test Number : C9560-654
Test Name : IBM Tivoli Application Dependency Discovery Manager V7.2.1.3 Implementation
Vendor Name : IBM
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Exam Title : IBM Certified Deployment Professional - Tivoli Application Dependency Discovery Manager V7.2.1.3
Exam ID : C9560-654
Exam Duration : 90 mins
Questions in exam : 68
Passing Score : 66%
Official Training : Tivoli Application Dependency Discovery Manager
Exam Center : Pearson VUE
Real Questions : IBM Tivoli Application Dependency Discovery Manager Implementation Real Questions
VCE practice questions : IBM C9560-654 Certification VCE Practice Test

Planning
- Given a list of initial business applications to be discovered, the list of servers the application runs on, and the approved project plan, determine the order, plan and methodology for discovery so that discovery scopes have been defined for discovering the servers and its components that the initial business applications run on.
- Given a customer's environment, design the architecture so that the initial architecture plan for the solution has been created.
- Given a customer's environment, determine the best estimate of the number of TADDM components required so that the initial architecture plan for the deployment has been created.
- Given the customer's network configuration / diagrams and TADDM solution architecture, define firewall requirements so that list of ports to be opened on firewalls is delivered.
- Given the list of technologies to be discovered and list of sensors that require credentials to run correctly, gather proper information from TADDM documentation, communicate to customer, implement and refine so that requirements for credentials are communicated and implemented in the environment
- Given SME(s) and/or documentation, determine and document the customer's existing environments that will be discovered and managed with TADDM so that an implementation plan is developed.
- Given server with operating System installed for TADDM Installation, verify OS configuration and required S/W or Libraries are installed on that server so that the server is available for TADDM installation.
- Given a list of computer systems/components/applications that will be discovered, create a list of TADDM sensors that will be run so that a list of sensors and any required credentials has been created.
- Given that TADDM defines the different levels of discovery, analyze data needs and explain to customers the different levels and the options that are available so that the customer understands the 3 levels of discovery available within TADDM.
- Given the customer's data source requirements, analyze the requirements to determine if Discovery Library Adapters (DLA) are necessary and a means to import and export data to/from TADDM so that the customer's environment has been evaluated for DLA requirements.

Installation
- Given a system ready for database creation, prepare the database for IBM Tivoli Application Dependency Discovery Manager (TADDM) using different operating system so that database preparation is completed.
- Given the TADDM architecture document and installation binaries, install TADDM and set up the environment so that TADDM is installed, initially configured, and up and running.
- Given a running TADDM environment, database backed up and binaries backed up, Install TADDM fix pack so that TADDM fix pack installation is completed successfully.
- Given an installed TADDM host, validate and complete the post installation configuration so that TADDM server will be ready for configuring the discovery.
- Given the proper access administrator authority for a designated anchor server, configure anchor servers so that a service account has been created that will be used by the anchor server for discovery behind the firewall.

Configuration
- Given target systems prepared for Anchor installation, list of anchors to be deployed with SSH servers installed, configure Anchors so that Anchor objects are created in IBM Tivoli Application Dependency Discovery Manager (TADDM) GUI and tested to be running.
- Given a running TADDM environment and a list of Windows Gateways to be configured, perform SSH server installation and configuration on target systems, create Windows Gateway objects in TADDM GUI so that Windows Gateways are configured properly and ready to be used during discovery.
- Given customer's need for the 3 levels of discover and a running TADDM system, create different levels of discovery profiles and enable the options that are available so that Configuration Items can be discovered.
- Given the list of extended attributes to be discovered by TADDM for chosen operating system, create and configure extended attributes by creating them, configuring templates and running a discovery so that extended attribute successfully populated with desired value.
- Given Target server(s), a working TADDM server and access to the Discovery Management Console, using either the UI or command line add a Scope Set with the machine(s) configured so that the machine(s) can be discovered.
- Given a list of servers / images and components/applications to be discovered, define the user privileges required for TADDM scans so that users with proper credentials are deployed to targets to be discovered and TADDM Access Lists are configured properly.
- Given the user name and password for access to machines, a working TADDM server, and access to the Discovery Management Console, navigate to the Discovery Management Console and add an access credential so that Configuration Items can be discovered.
- Given the need to debug Sensors more efficiently and effectively, set the SplitSensor option so that a clear view of each sensor is available.
- Given a custom design file, configure the customBusiness Intelligence and Reporting Tool ( BIRT) report so that custom BIRT report is generated for the collected data.
- Given a running TADDM environment and a database connection, generate a report so that a report is generated.
- Given the list of Windows systems that will be discovered with a non-admin account and the account name to be created, configure the windows target for non-admin discovery so that Windows system is discovered Level2 using non-admin account.
- Given the discovery schedule, configure TADDM scheduling so that discovery starts at a given time.
- Given an installed TADDM server, create the snapshots to take a point-in-time copy of basic information about computer systems, discovery events and server applications running on computer systems so that the snapshots are available to take a point-in-time copy of basic information
- Given a list of locations to be configured in TADDM, make necessary decisions and modifications in collation.properties and anchor properties files so that discovered components have location tag attribute set properly.
- Given the information required to create a custom server template, a running TADDM, server and access to the Discovery Management Console, define custom server templates and build custom server templates from the UI so that the custom applications have been discovered properly.
- Given that TADDM and IBM Tivoli Monitoring (ITM) are installed, prepare ITM and TADDM environment so that discovery can be performed by using ITM agent.
- Given a business application and the list of servers/components/applications that compose the business application, create the appropriate application descriptor files and deploy them to the appropriate directories on the servers where discovery will be done so that discoveries have been run and it has been Checked that the business application has been built correctly.
- Given a list of users to be created and Admin access to Data Management Portal, create users so that TADDM user IDs have been configured for use.

Administration
- Given the need to categorize application components into business applications and services, create business application and services using the Data Management Portal that combines large collections of individual components into logical groups.
- Given a properly installed and operating IBM Tivoli Application Dependency Discovery Manager (TADDM) system and access credentials, execute API query so that XML data is extracted and available via STDOUT (Standard Output).
- Given the timespan for keeping the historical changes of attributes values, perform a cleanup of the database by running proper SQLs so that TADDM database is cleaned up from old change history data
- Given TADDM is up and running, max size of the file system to be used for logs, configure collation.properties settings for logs maintenance and optionally implement removing sensor logs mechanism so that log files are maintained automatically.
- Given a customer's need for TADDM, prepare, install, and execute TADDM so that the customer's environment is fully discovered and validated.
- Given a list of servers/images and components/applications to be discovered, manage and obtain credentials so that credentials are created on the requested servers/images/components/applications.
- Given an existing scope and discovery profile to use, run a TADDM discovery using the Discovery Management Console and the API so that a discovery has been run by using the API and Discovery Management Console.
- Given a valid IDML file for loading, a running TADDM server and access to the server running TADDM, use the loadidml script to populate the TADDM database so that the information contained in the IDML file is loaded into the TADDM database.
- Given a TADDM Server, Discovery Management Console and User ID and password, review the types of status messages that occur during discovery and viewing history so that the status messages are understood.
- Given an installed TADDM server, access to the server running TADDM and the new database user password, update the collation.properties file and encrypt the database access passwords so that the collation.properties file is updated with the new encrypted passwords.
- Given an installed TADDM server and terminal access to the server running TADDM, start and stop the TADDM server processes so that the TADDM server has been stopped or started.
- Given the TADDM server is running, run the analytics from the Data Management Portal so that the necessary information is available to be analyzed.
- Given a working TADDM server, and access to the Data Management Portal, navigate to the Data Management Portal and create Configuration Items, and dependencies so that a new Configuration Item (CI) or dependency is created.
- Given that the present roles do not suffice for an access requirement to TADDM, create a new role with unique permissions to fulfill the request so that a new TADDM role is configured for use.
- Given supported hardware, operating system and running database, command-line access to the TADDM server, the password for the root, create backups and perform restores so that a backup and restore are available when needed.

Problem Determination
- Given a running IBM Tivoli Application Dependency Discovery Manager (TADDM) environment and database connectivity, tune the Discovery parameter so that the discovery parameters are tuned appropriately.
- Given list of Java Virtual Machines to set extended logging for, edit collation.properties file and set proper values for logging level so that logging level is set to desired value and logs contain desired information for problem diagnosis
- Given that a problem has occurred within the TADDM environment and error levels need to be modified to ensure the correct messaging is captured for remediation enable/disable advanced logging for TADDM so that the environment is set for debug mode so that when problem occurring the correct messaging is captured and resolved.
- Given the need to diagnose a problem within the TADDM environment, utilize the support bin tools so that problem can be debugged.
- Given TADDM is installed and user IDs are created and problems occur with Discover, Topology, Discovery Admin, Proxy or Gigaspace processes, review the jvmarg settings in the collation.properites file and determine if more memory is required so that performance is enhanced and/or service is not interrupted.
- Given the need to define common parameters in the collation.properties files, review the most common parameters that are located in the collation.properties file so that the common parameters have been defined.
- Given a TADDM server, Identify points of failure regarding NMAP on L1 discoveries so that points of failure regarding NMAP on L1 discoveries are identified and corrected.
- Given an application sensor failure, conduct an L3 Scan and troubleshoot application sensor failures so that the problems are resolved for a successful L3 collection.



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IBM and Pfizer trust computer discovering Can Predict Alzheimer’s chance | C9560-654 exam Questions and exam Braindumps

IBM and Pfizer trust computer gaining knowledge of Can Predict Alzheimer’s risk

posted: Oct. 22, 2020

through Mark Terry

BioSpace

Researchers with Pfizer and IBM developed a man-made intelligence (AI) mannequin that they claim can predict the eventual onset of Alzheimer’s sickness with seventy one% accuracy in line with a language pattern. They posted the analysis these days within the Lancet eClinicalMedicine.

The AI works on linguistic evaluation. The analysis group leveraged a short, non-invasive language demo based on a common verbal cognitive verify Alzheimer’s patients are given, the cookie-theft picture-description assignment. The examine is used to consider cognitive impairment in a lot of neurological disorders, together with stroke and Alzheimer’s ailment. The AI mannequin’s comments became stronger than medical-scale predictions in line with biomedical information which are correct about 59% of the time.

The investigators used long-term longitudinal information from the Framingham coronary heart analyze, a multi-generational examine launched in 1948. They were in a position to examine their model’s predictions towards exact results. IBM notes, “if the AI model analyzed a speech demo from a participant on the age of sixty five and expected they would increase with the aid of the age of 85, researchers could then verify data to examine whether a analysis had in reality took place.”

IBM research additionally announced a linked mission with the countrywide Institutes of fitness to investigate speech to determine risk components for schizophrenia and psychosis.

The Alzheimer’s association indicates that greater than 5 million individuals within the U.S. of all ages have Alzheimer’s disease. each and every state is projected to event at least a 14% increase within the prevalence of Alzheimer’s disorder between 2017 and 2025. There are just a few easy methods to predict the possibility of Alzheimer’s.

In previous work, IBM tested AI to determine proteins to foretell the awareness of beta-amyloid, a protein that accumulates abnormally in the brains of Alzheimer’s patients. other researchers, akin to those at Unlearn.AI, lately posted research describing a device to assume Alzheimer’s progression, describing a roadmap of indicators. a group of scientists on the school of California, Berkeley, outlined an AI gadget to predict Alzheimer’s from mind scans up to 6 years forward of medical prognosis.

Cineberg / Shutterstock

besides the fact that children, IBM and Pfizer differentiate from outdated work, generally since it was based on records accumulated before the courses within the analyze showed their first indications of cognitive impairment. They also evaluated the chance of Alzheimer’s in the regularly occurring inhabitants, as adversarial to in excessive-risk organizations.

of their examine, they evaluated 703 samples from 270 contributors. Half of the contributors developed Alzheimer’s before eighty five years of age. In inspecting their language, they took into consideration greater than 87 variables, including misspellings, punctation, uppercase usage, verbosity, lexical richness, and repetitiveness. They also regarded age, gender, education, visuospatial and govt reasoning, objective naming, reminiscence, consideration, abstraction, and effects from the Montreal cognitive assessment MoCA.

They analyzed transcriptions of the sufferers’ herbal language processing, comparing to facts from the Framingham heart study. The Framingham examine protected americans who have been assessed with the two-minute Mini-intellectual State Examination speech check every 4 years along with neuropsychological tests each year when a family member first mentioned signs of possible cognitive decline.

In a blog post, the researchers observed they plan to leverage datasets that extend on the geographic, socioeconomic, and racial diversity of courses as they continue their analysis. “This breadth of records is commonly very difficult to return with the aid of when it comes to ailment prediction, and access to it allowed us to instruct these fashions with precision. They [will] continue to coach their algorithms while at all times respecting core concepts of privacy, transparency, and consent.”

as the authors referred to of their article, “The purpose of this examine is to look at various to what extent linguistic efficiency at a single time point can be utilized as a prognostic marker of conversion to advert…. using the variables acquired when the individuals had been assessed to be cognitively normal, they developed models to foretell even if or not a particular participant will Boost MCI [mild cognitive impairment] because of advert on or earlier than eighty five years old.”

possibly most astounding, given increased success in finding biomarkers to establish Alzheimer’s, the authors noted, “Our effects exhibit that it's feasible to foretell future onset of Alzheimer’s disorder the use of language samples acquired from cognitively normal people. additionally, they confirmed that using linguistic variables from a single administration of the cookie-theft picture description task performed more advantageous than predictive fashions that included APOE, demographic variables, and NP examine effects.”

BioSpace supply:

https://www.biospace.com/article/ibm-and-pfizer-consider-laptop-learning-can-predict-alzheimer-s-chance


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