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Test Number : C2070-981
Test Name : IBM FileNet Content Manager V5.2- Specialist
Vendor Name : IBM
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Exam Title : IBM Certified Specialist - FileNet Content Manager V5.2
Exam ID : C2070-981
Exam Duration : 120 mins
Questions in test : 72
Passing Score : 47 / 72
Official Training : IBM Content Navigator (IBM Content Management Information Center)
IBM FileNet P8 V5.2 Information Center
Exam Center : Pearson VUE
Real Questions : IBM FileNet Content Manager Real Questions
VCE practice test : IBM C2070-981 Certification VCE Practice Test

Architecture and Planning
- Demonstrate knowledge of the core components for CPE, WPXT, CSS and Content Navigator
- Demonstrate knowledge of Content Manager scalability concepts
- Demonstrate knowledge of high availability concepts
- Demonstrate knowledge of disaster recovery concepts
- Demonstrate knowledge of prerequisite tasks and the use of the installation/upgrade worksheet
- Demonstrate an understanding of a FileNet P8 domain
- Demonstrate knowledge of platform communications (core engines and infrastructure components)
- Demonstrate knowledge of the APIs and available transports
- Demonstrate basic knowledge of P8 dependencies to directory servers, database servers and storage devices 24%
Installation and Configuration
- Demonstrate an understanding of installing a single-server and a distributed system
- Demonstrate knowledge of the Configuration Manager tool
- Show an understanding of the IBM Content Navigator Configuration and Deployment tool
- Demonstrate knowledge of security accounts used for configuration
- Demonstrate an understanding of Content Platform Engine client files 11%
Administration
- Demonstrate an understanding of backup and restore
- Demonstrate knowledge of IBM FileNet P8 component startup and shutdown
- Demonstrate an understanding of WorkPlace and WorkPlace XT site/user preferences
- Demonstrate knowledge of workflow system configuration
- Demonstrate an understanding of Content Based Retrieval (CBR)
- Demonstrate knowledge of using Content Engine query builder
- Demonstrate knowledge of using Consistency Checker
- Demonstrate knowledge of monitoring with IBM System Dashboard
- Show knowledge of using the IBM Administration Console for Content Platform Engine (ACCE)
Show an understanding of performing bulk move content jobs
Demonstrate knowledge of object retention and disposition
Demonstrate knowledge of Component Manager
- Show knowledge of administering IBM Content Navigator 25%
Repository Design and Management
- Demonstrate an understanding of repository design concepts
Demonstrate knowledge of classes, properties, choice lists, folders, object stores, and life cycle management
Demonstrate knowledge of Content Federation Services
- Demonstrate an understanding of Content Platform Engine events: actions and subscriptions
- Demonstrate knowledge of search and entry templates
- Demonstrate an understanding of auditing
- Show an understanding of storage area activation
- Demonstrate an understanding of storage areas, content encryption and compression 18%
Deployment
- Demonstrate an understanding of the deployment process
- Demonstrate knowledge of the FileNet Deployment Manager
- Demonstrate an understanding of using the import/export manifest 5%
Security
- Demonstrate an understanding of authentication and authorization concepts
- Demonstrate knowledge of securing content using ACLs, security inheritance, marking sets and security proxies
- Demonstrate knowledge of Workplace XT access roles
- Demonstrate an understanding of security caching 7%
Troubleshooting and Performance Tuning
- Demonstrate knowledge of using Content Platform Engine trace logging and client API tracing
- Demonstrate knowledge of using log4j and application server logging
- Demonstrate knowledge of verifying and troubleshooting installations and upgrades
- Demonstrate knowledge of evaluating and applying system fix packs
- Demonstrate knowledge of performance tuning the Content Platform Engine
- Show an understanding of content search optimization 8%



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IBM FileNet Latest Questions

The Very Human Labor That Powers artificial Intelligence | C2070-981 test Questions and braindumps

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In 2015, Caroline Sinders become working as a design researcher at IBM when she began to have questions about how Watson, the enterprise’s synthetic intelligence system, changed into being developed. AI programs like Watson have to be “trained” with statistics sets—as an example, given a huge batch of Tested pictures of cease signals from diverse angles, in different lighting fixtures, and of different satisfactory to be in a position to appreciate cease signs on their personal. Sinders turned into curious about these records units: The procedure of accurately categorizing thousands and thousands of information elements appeared like a herculean task in its personal right; the place, precisely, changed into all this statistics coming from?

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“a lot of my coworkers were like, ‘I don’t recognize why you’re asking us these questions, we’re just presupposed to construct this device out,’” she recalls.

while Sinders’s coworkers may additionally have been in a position to push the query aside, discovering the answer of the place the information units necessary to instruct artificial intelligence methods come from at last led her to the area of crowd-working systems. Amazon’s Mechanical Turk and different platforms similar to Fiverr, Clickworker, Microworker, and Crowdcloud permit employers to present worker's repetitive, task-based mostly assignments at flat prices. as a result of the entire work is digital, worker's from everywhere perform projects on these platforms—and on account that crowd-laborers are considered unbiased contractors, minimal wage legal guidelines don’t follow.

synthetic intelligence systems, Sinders found, still rely upon very human grunt work for their uncooked fabric. as an example the human cost of artificial intelligence—the thousands and thousands of hours of work which have gone, and proceed to head, into making essentially the most profitable AI viable—Sinders created the Technically responsible capabilities Wage Calculator.

Crowdlabor

As its identify suggests, the TRK Wage Calculator makes it possible for clients to calculate salary for crowd-working assignments. The calculator aspects three sliders: variety of photos to label (labeling information is a common task in artificial intelligence development), expense per assignment, and time per assignment. The effects are bleak. according to the calculator, a normal task, labeling three,200 images for 32 cents each and every at a pace of two minutes per photograph, would yield a worker less than $63 per day—which, the calculator features out, works out to under minimal wage in Washington, the state during which Amazon is headquartered.

The TRK Wage Calculator does not seize the entire complexity of crowd-working, neither is it supposed to. while most people on Mechanical Turk stay in the u.s. (there are greater than 1,000,000 people worldwide), it goes with out asserting that they aren’t all found in Washington. The vicinity became selected by using Sinders since it is each the state with the maximum minimal wage in the u.s. and residential to Amazon. These particulars make contributions to the concept of the TRK Wage Calculator as a “mathematical provocation,” instead of a genuine tool—an clever approach of calling out Amazon for permitting the ruthless exploitation of people, which it might effortlessly avoid via environment parameters for pricing. (Amazon didn't reply to distinct requests for remark for this article.)

Sinders created the TRK Wage Calculator as part of her residency with the Mozilla basis. The groundwork is accountable for the construction of the Firefox web browser and, greater frequently, is dedicated to keeping the cyber web open and available. Sinders’s immediate all through her residency turned into to discover artificial intelligence, which she determined to pursue on account of lingering questions from her time at IBM and her personal ongoing undertaking, Feminist facts Set, examining how the development of synthetic intelligence can combine feminist values like fair compensation.

existing situation

“using intersectional feminism as a way to interrogate machine studying—that’s an interrogation of the way you label and body information,” she explains. “So you then need to feel about labor, appropriate?”

For extra standpoint into the development of artificial intelligence, Sinders joined Mechanical Turk as a employee and interviewed other crowd-employees in the u.s. and India. (After the U.S., India is the 2d most popular nationality of employees on Mechanical Turk.) The journey and interviews revealed how even an apparently fruitful crowd-working assignment can develop into a morass of additional initiatives.

“What i realized changed into that point isn’t definitely listed a great deal within the interfaces, however time is an immense component of how you do work,” Sinders explains.

With crowd-work priced per task or per project, the period of time involved is obscured. A $50 assignment may contain six hours of labor—or sixteen hours of work. the former is someday of work at the federal minimal wage in the u.s.; the latter is 2 days of labor well under the minimum wage (or one especially hellish day of time beyond regulation on the same fee). Even smartly-meaning employers on crowd-sourcing systems may additionally underestimate the amount of time indispensable to finished their assignments, specifically if they lack adventure completing the tasks themselves and fail to account for realities like fatigue, to claim nothing of damage time for nutrition or bathing room visits. Such precise misestimation is compounded by using outright lowballing, resulting in Mechanical Turk people’ incomes an estimated $2 per hour on normal.

“if you don’t suppose about time, it doesn’t account for the way you can be paid radically differently,” says Sinders. “If somebody had been like, ‘Please label these 1,000 images and right here’s $50,’ that may additionally sound really good firstly—apart from if you ask how long it takes.”

anyway Mechanical Turk, probably the most other crowd-working structures that Sinders focused on when creating the TRK Wage Calculator turned into CrowdFlower, which became received by way of Appen in 2019. Appen now provides artificial-intelligence-connected functions to Amazon, Microsoft, Adobe, and other tech businesses.

“Appen collects and labels pictures, textual content, speech, audio, video, and different statistics used as working towards records to build and perpetually increase synthetic intelligence systems,” explains Brian Reavey, a director on the enterprise. “Our platform permits valued clientele to specify initiatives needed for his or her certain mission. for instance, a corporation engaged on voice instructions to enrich a automobile’s infotainment system could request spoken words or phrases which are established whereas using a car in loads of languages and dialects.”

“we've over 1 million crowd-people all over the world,” says Reavey, “and their ‘Crowd Code of Ethics’ is their commitment to pay reasonable wages to all members of the crowd.”

whereas Reavey touts Appen’s code of ethics, the commitment involving fair pay is vague, mentioning only that it's the company’s aim to pay above minimum wage. Appen says that it tries to agree to local minimal wage standards in the one hundred thirty-plus countries where it operates by way of using AI to predict how long selected initiatives may still take—which most effective brings us full circle returned to the black container of AI development, and Sinders’s first question of where IBM’s statistics sets had been coming from. Yet no matter if Appen is as rigorous in its determination of minimal wage as the TRK Wage Calculator is precisely the type of question that Sinders hoped to elicit together with her task.

“It may also be used by using worker's themselves as an advocacy tool,” she explains, “but i used to be more attracted to making an attempt to have smaller birth-ups, analysis labs, artists, and individuals who use issues like Mechanical Turk, Fiverr, and CrowdFlower in reality understand that after they present to pay for work, in the event that they don’t have an realizing of time and how much that work truly expenses, they are complicit in underpaying.”


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