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IBM C2090-621 : IBM Cognos Analytics Author V11 Exam

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Test Number : C2090-621
Test Name : IBM Cognos Analytics Author V11
Vendor Name : IBM
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C2090-621 exam Format | C2090-621 Course Contents | C2090-621 Course Outline | C2090-621 exam Syllabus | C2090-621 exam Objectives

Exam ID : C2090-621
Exam Title : IBM Cognos Analytics Author V11
Number of questions: 60
Number of questions to pass: 42
Time allowed: 90 mins
Status: Live

Dashboards 15%
Explain designing for mobile use
Describe how to create simple Dashboards
Describe how to create complex interactive Dashboards
Describe how to modify Dashboards
Demonstrate how to control Dashboard data

Reports 45%
Describe how to create list reports
Describe how to apply filters
Describe how to use prompts
Describe using conditional formatting
Describe using calculations and macros
Describe how to use markers
Demonstrate presenting data graphically
Demonstrate using HTML and XML
Describe using Crosstabs
Explain designing for mobile use
Describe using reusable objects
Describe using layout control
Demonstrate combining multiple related objects
Explain using interactivity

Active Reports 16%
Describe how to create report connections
Describe using using Charts, Visiualizations and Decks
Describe designing for mobile use
Demonstrate managing controls and variables

Data 20%
Explain connecting to the Data source
Describe how to use Data sources
Explain the differences between using Data modules and Framework Manager packages on a report
Describe using data shaping
Explain creating reports using an SQL statement

Distributing Reports 4%
Describe using bursting

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IBM is using gentle, as an alternative of electricity, to create extremely-quick computing | C2090-621 exam Braindumps and exam Cram

To quench algorithms' reputedly limitless thirst for processing power, IBM researchers have unveiled a new strategy that may imply massive adjustments for deep-gaining knowledge of applications: processors that operate computations totally with easy, as opposed to electricity.  

The researchers have created a photonic tensor core that, based on the residences of gentle particles, is capable of processing statistics at unheard of speeds, to carry AI functions with ultra-low latency.  

besides the fact that children the device has only been demonstrated at a small scale, the file suggests that as the processor develops, it could achieve a thousand trillion multiply-accumulate (MAC) operations per second and per rectangular-millimeter – in line with the scientists, that is 2 to a few orders greater than "state-of-the-paintings AI processors" that depend on electrical indicators.  

SEE: Kubernetes safety e book (free PDF) (TechRepublic)

IBM has been engaged on novel tactics to processing instruments for a couple of years now. part of the business's analysis has concentrated on establishing in-memory computing technologies, in which memory and processing co-exist in some kind. This avoids transferring records between the processor and a separate RAM unit, saving energy and cutting back latency. 

final year, the enterprise's researchers unveiled that they had effectively developed an all-optical strategy to in-memory processing: they built-in in-memory computing on a photonic chip that used easy to carry out computational initiatives. As a part of the experiment, the team established that a basic scalar multiplication might simply be performed the usage of the technology. 

In a new weblog post, IBM research workforce member Abu Sebastian shared a new milestone that has now been completed the use of mild-based mostly in-memory processors. Taking the know-how to the next stage, the team has constructed a photonic tensor core, which is a sort of processing core that performs refined matrix math, and is specially suitable for deep-gaining knowledge of functions. The gentle-based mostly tensor core was used to perform an operation called convolution, this is constructive to procedure visual data corresponding to images. 

"Our experiments in 2019 were generally about showing the knowledge of the know-how. A scalar multiplication is very removed from any actual-lifestyles software," Abu Sebastian, research team of workers member at IBM analysis, tells ZDNet. "however now, we've a whole convolution processor, which you could probably use as part of a deep neural network. That convolution is a killer application for optical processing. In that feel, it's quite a large step." 

probably the most huge competencies that mild-based mostly circuits have over their digital counterparts is never-before-seen velocity. Leveraging optical physics, the know-how developed with the aid of IBM can run complicated operations in parallel in a single core, the use of diverse optical wavelengths for every calculation. combined with in-reminiscence computing, IBM's scientists achieved extremely-low latency it's yet to be matched through electrical circuits. For functions that require very low latency, for this reason, the pace of photonic processing might make a large difference. 

Sebastian places ahead the illustration of self-using cars, where speed of detection might have lifestyles-saving implications. "if you're using on the motorway at 100 miles-per-hour, and also you should detect some thing inside a certain distance – there are some instances where the present technology does not allow you to do that. however the kind of velocity that you simply get with photonic-based mostly systems is a number of orders of magnitude stronger than electrical approaches." 

SEE: This powerful new supercomputer will let scientists ask 'the right questions'

With its means to operate a few operations simultaneously, the gentle-based processor developed by means of IBM also requires much less compute density. in accordance with Sebastian, this may be one other key differentiator: there will be some extent, says the scientist, where loading car trunks with rows of generic GPUs to help ever-extra refined AI programs might not cut it anymore.  

With most big motor vehicle businesses now opening their personal AI research facilities, Sebastian sees self reliant vehicles as a key application for light-primarily based processors. "there is a true want for low latency inference in the area of self sufficient using, and no technology that may meet it as of now. it's a special probability." 

IBM's team, even though it has efficaciously designed and confirmed a magnificent core, still should lengthen trials to make sure that the expertise can be built-in at a equipment level to be certain end-to-end performance. "We need to do plenty greater there," says Sebastian; but in response to the scientist, work is already underway, and as research continues, extra applications are best more likely to arise. buying and selling electrical energy for easy, in the container of computing, certainly makes for a spot to watch. 

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