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C2070-982 exam Dumps Source : IBM Case Foundation V5.2, Specialist

Test Code : C2070-982
Test name : IBM Case Foundation V5.2, Specialist
Vendor name : IBM
: 116 existent Questions

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IBM’s ‘large guess’ on Kubernetes is unifying cloud providers throughout platforms | killexams.com existent Questions and Pass4sure dumps

Navigating cloud computing functions can likewise be intricate, particularly when they compass from several suppliers. hence, setting up a superior groundwork turns into even more principal in maintaining a success operations across today’s multicloud panorama. For IBM, that basis is Kubernetes, the open-source tool for managing containerized application applications at scale.

“IBM has taken a tremendous pot on Kubernetes two and a half years ago,” referred to Daniel Berg (pictured), several engineer, IBM Cloud Kubernetes provider, at IBM. “[We] on no account basically looked back; it’s their simple basis for their platform services.”

Berg spoke with Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s cellular livestreaming studio, totality the way through the IBM suppose adventure in San Francisco. They mentioned IBM’s Kubernetes functions and the company challenges of poignant operations between inner most and public clouds. (* Disclosure beneath.)

Bridging the multicloud hole

The IBM Cloud Kubernetes provider at the jiffy has two distributions: IBM Cloud deepest, or ICP, which operates on-premises, and a managed service in the public cloud. So, what are the benefits of completely keeping a private cloud with Kubernetes? The container administration platform modernizes and organizes years-ancient content material.

“We’ve modernized it, set aside it in containers, install it, and control it on Kubernetes. The first-class factor is that content you can carry on-premises where it’s vital essentially the most and speed it in ICP — and likewise tangle that and speed it in their public cloud,” Berg defined.

Kubernetes is facile to installation, install, and score totality started. despite the fact, it isn't without its problems. With enhanced proliferation comes enhanced issue in managing the distinctive clusters, Berg cited. “There are nonetheless some complexities, as a result of … you’ve received construction clusters; you’ve bought verify clusters,” he pointed out.

To alleviate the issue, IBM launched a brand fresh product referred to as Multicloud supervisor, which provides a handle aircraft to maneuver substances throughout various clouds and disparate platforms. it really works with ICP and IBM Kubernetes provider however is additionally compatible with Amazon, Google, Azure and OpenShift. Multicloud supervisor additionally helps with security compliance and enforcement, so it provides safety anywhere it's missing.

For corporations discovering it under feasible to preserve consistency and requirements whereas customizing for specific information needs, Berg cited the advantages of assorted distributions. “if you would fondness anything that’s totally, incredibly particular to a given spend case or you bear variations in your infrastructure that you simply need to bear more flexibility, that’s the state IBM Cloud private comes in,” he talked about.

Two clouds are improved than one

moving to public cloud in a single fell swoop is a Herculean project, even for massive organizations corresponding to Amazon and Google. this is where hybrid cloud is available in. In IBM’s case, it combines ICP and OpenShift to give OpenShift users IBM’s content material, integrated monitoring, and integrated logging onto the platform for which they're already standardized.

“as a result of they constructed and are standardized on Kubernetes, they give Kubernetes carrier and they carry out this at scale and comfy, as well as incredibly available,” Berg stated.

Berg did warn against the spend of only 1 cloud vendor, and he additionally informed agencies to be consistent in what they want out of their suppliers. “but the factor that consumers carry out should examine, and what they carry out deserve to standardize across an business, is a few of the core tenets and core applied sciences,” he brought.

Visibility into workloads is additionally principal to a corporation’s operations, Berg explained. And IBM Cloud Monitoring does this. The device is not enjoyable to Kubernetes, either. quite, it can likewise be extended into virtual machines and several kinds of workloads. IBM’s monitoring is greatly helped by its partnership with Sysdig Inc., Berg added.

“that you may’t build a cloud-native solution devoid of monitoring, correct? Monitoring and log … it’s fondness peanut butter and jelly. You’ve got to bear them,” Berg concluded.

Watch the comprehensive video interview below, and figure sure to tangle a inspect at more of SiliconANGLE’s and theCUBE’s coverage of the IBM judge experience. (* Disclosure: IBM subsidized this section of theCUBE. Neither IBM nor different sponsors bear editorial control over content material on theCUBE or SiliconANGLE.)

picture: SiliconANGLE considering the fact that you’re privilege here …

… We’d want to uncover you about their mission and the way that you can assist us fulfill it. SiliconANGLE Media Inc.’s enterprise mannequin is in response to the intrinsic price of the content, now not advertising. unlike many on-line publications, they don’t bear a paywall or speed banner promoting, as a result of they are looking to preserve their journalism open, without bear an outcome on or the should chase traffic.The journalism, reporting and commentary on SiliconANGLE — along with are living, unscripted video from their Silicon Valley studio and globe-trotting video teams at theCUBE — tangle loads of challenging work, time and funds. preserving the excellent inordinate requires the aid of sponsors who're aligned with their imaginative and prescient of ad-free journalism content material.

in case you just fondness the reporting, video interviews and other ad-free content material privilege here, please tangle a second to check out a sample of the video content material supported by means of their sponsors, tweet your help, and retain coming again to SiliconANGLE.

Cloud IDE evaluate: AWS Cloud9 vs. Eclipse Che vs. Eclipse Theia | killexams.com existent Questions and Pass4sure dumps

Bringing on a fresh developer to a programming assignment with many dependencies can now and again be a nightmare. I’ve viewed an intense case where the enterprise ultimately gave up and purchased the developer a fresh computing device after a month of considerations making an attempt to configure his ancient one. extra generally, setting up a brand fresh construction ambiance for a brand fresh developer could tangle between three days and two weeks.

That difficulty is likely one of the motivations for web-based developer workspaces. an extra motivation is that machines for local construction need gigantic CPU and RAM elements, which raise the cost of hardware; those components enable the developer to build the challenge expeditiously. computers for having access to web-based workspaces can score away with lower-end hardware than computer systems for local construction.

As an additional advantage, net-based mostly developer workspaces can centralize and standardize a configuration. How many times bear you ever heard “it really works on my computer” in keeping with a bug report? Standardized environments can dispose of that issue.

in this article I’ll contend three cloud IDEs that deliver web-primarily based developer workspaces. Two of them—Eclipse Theia and Eclipse Che—are pretty fresh free-open-supply projects presently under the auspices of the Eclipse groundwork. The third —AWS Cloud9—is an older product it's now owned through and built-in with Amazon web capabilities.

Eclipse Theia

Eclipse Theia is an open-supply venture to supply the visual Studio Code development event in a browser; it can additionally speed on the computer in the Electron shell. Theia depends on visible Studio Code’s Language Server Protocol to provide language-selected code completion and the other features they expect in a modern code editor.

because it can tangle skills of the language servers written for visible Studio Code, Theia has entry to more than 60 available language servers together with JavaScript, Java, Python, and TypeScript. Theia likewise supports the debug adapter protocol.

Theia itself is written in TypeScript and makes spend of PhosphorJS because the foundation for its shell and its draggable dock layouts. It integrates a terminal that reconnects on browser reload to retain the command-line history. that you can create your own extensions to Theia if you want.

There are three principal tips on how to are attempting Theia. One is to speed it in Docker:

docker speed -it -p 3000:3000 -v “$(pwd):/domestic/undertaking:cached” theiaide/theia:next

The 2d is to speed it in Gitpod (see sidebar and screenshot under). The third is to speed Eclipse Che version 7 or later (see the subsequent area), which makes spend of Theia as its UI as a substitute of the Java UI utilized in older types of Che.

The Eclipse Theia mission comprises contributions from TypeFox, Ericsson, crimson Hat, IBM, Google, and ARM. The project roadmap contains a plug-in system to steer VS Code extensions (beyond language servers), integration with trying out frameworks, and different advancements.

eclipse theia gitpodIDG

within the screenshot above we're operating Theia in a browser on the GitHub theia-ide/theia mission, by the spend of Gitpod. word Theia’s similarity to visual Studio Code in each elements and look. additionally be conscious that Gitpod automatically developed the task within the terminal window.

Eclipse Che

Eclipse Che is an open source developer workspace server and cloud IDE designed for teams and agencies. Che edition 7, presently in beta, uses Eclipse Theia because the foundation of its IDE. Older types of Che spend a GWT-primarily based IDE. Che workspaces speed in containers on Docker, OpenShift, or Kubernetes.

that you can speed Che within the public cloud, a non-public cloud, or deploy it on any working system. Che has been verified on Ubuntu, Linux, MacOS, and home windows. that you can additionally speed Che in a self-provider workspace hosted at https://che.openshift.io/, for which you’ll should bear or create a free OpenShift or crimson Hat log-in.

in addition, Eclipse Che comprises the core of red Hat CodeReady Workspaces, the brand fresh construction atmosphere for OpenShift. besides being supported via red Hat, CodeReady Workspaces bear pre-constructed stacks with supported red Hat applied sciences and consist of red Hat SSO to address authentication and safety between the developer groups.

The Eclipse Che assignment contains contributions from more than 20 businesses including CodeEnvy (the fashioned developer of Che), Docker, IBM, red Hat, and TypeFox. The Che roadmap comprises finishing the Theia integration and the plug-in methods for Theia and Che.

eclipse cheIDG

in this screenshot they are working Eclipse Che 6 in a browser, hosted on che.openshift.io, with a Node.js stack. The mission is a “whats up, World!” web app in keeping with Node.js and specific.

AWS Cloud9

The Cloud9 IDE, which i mentioned as a fade IDE in 2017, now belongs to Amazon internet services. besides having a browser-based mostly, multi-language code editor, debuggers for a few languages, and a terminal that’s pre-licensed for AWS capabilities, Cloud9 now permits for collaborative coding.

which you could speed Cloud9 construction environments on managed Amazon EC2 circumstances or any Linux servers that assist SSH. Cloud9 comprises tooling for upwards of 40 programming languages, youngsters best five bear debuggers, seven bear linting, and 12 bear code completion.

in case you speed Cloud9 on EC2, the EC2 instance will cease immediately after you immediate Cloud9, through default after half-hour, and your code will persist in Amazon EBS storage. in case you speed Cloud9 in your personal Linux server, the code will persist in native storage. in case you restart Cloud9 after its underlying instance has stopped, Cloud9 will instantly restart the example and restoration your edit session where you left off.

that you may conveniently populate a Cloud9 instance from a repository or from native info. within the screenshot under, I used Git from the Cloud9 command line to check out the GitHub repository for Keras. if you are enhancing a mission in line with a repository for which you bear relegate permission, which you can supersede the repo and tow changes as obligatory from the command line. Cloud9 doesn’t bear graphical support for edition control.

word the silhouette view on the rectify of the screenshot below, which works nicely for improper navigation inside a file. The fade menu shown on the excellent left works properly for more usual navigation. There is not any refactoring functionality in Cloud9, however there's standard code reformatting.

AWS Cloud9 is integrated with Amazon Lightsail, AWS CodeStar, AWS Lambda capabilities, and AWS CodePipeline. The Lambda integration seems to be notably decent.

aws cloud9IDG

AWS Cloud9 IDE showing Keras Python code cloned from GitHub. be conscious the define view at the rectify and the alternate options on the fade menu. The keyboard shortcuts proven are for MacOS.

Which cloud IDE?

Eclipse Theia, Eclipse Che, and AWS Cloud9 totality aid you edit and debug code in several programming languages from a browser. There are variations within the layout and performance, but now not satisfactory to matter unless you wish to accomplish something pretty advanced, equivalent to refactoring.

Cloud9 is an in particular decent option if you are engaged on AWS tasks, and Che is an in particular excellent preference (as CodeReady) if you're engaged on code for pink Hat systems. Theia gives the nicest modifying atmosphere of the three, however once Che 7 comes out of beta it will bear a Theia IDE as smartly.

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Clarify Health CEO to Present at HIMSS19 on The Future of custody Delivery | killexams.com existent questions and Pass4sure dumps

SAN FRANCISCO--(BUSINESS WIRE)--Feb 13, 2019--Healthcare providers are increasingly being held accountable for the cost, quality, and outcomes of custody – yet they need the proper tools and insights to be successful. Clarify Health Solutions, Inc., a pioneer in AI-enabled custody optimization, will be sharing strategies and tactics for tackling this industry challenge at HIMSS19 on Wednesday, February 13 at 3:00 p.m. (EST) in the IBM Theater (booth #6459).

In this session, Jean Drouin, MD, CEO and founder, will explore how the future of patient custody will be built on predictive analytics, precision workflows, and personalized risk management.

This session will likewise highlight how:

- Clarify Health is structure the foundation for the digital custody guidance of the future.

- Integrating the privilege data sources and applying machine learning enables game changing predictive analytics

- SBDoH data can power the most precise risk-stratification and case-mix adjustment in the industry

- To turn AI generated insights into action

- These four capabilities power a real-time custody guidance platform that is changing custody delivery across the US

Clarify Health provides the breakthrough technology and analytics platform to personalize and optimize patient custody journeys. Their purpose-built solutions - developed by a world-class team of data scientists and engineers from the monetary services industry, top clinical operations experts, and logistics specialists - are transforming healthcare processes and workflows. Clarify delivers actionable insights that enable physicians, health systems, payers, and life sciences organizations to deliver better custody today and evolve for a value-based world.

View source version on businesswire.com:https://www.businesswire.com/news/home/20190213005100/en/

CONTACT: Clarify Health

Kendall Reischl





SOURCE: Clarify Health Solutions, Inc.

Copyright industry Wire 2019.

PUB: 02/13/2019 06:00 AM/DISC: 02/13/2019 06:01 AM


Copyright industry Wire 2019.

AI Weekly: Trump’s American AI Initiative lacks substance | killexams.com existent questions and Pass4sure dumps

It’s been an eventful week in tech. Amazon announced it would abandon plans to open one of its two HQ2 locations in fresh York City, and the company likewise acquired Wi-Fi mesh network startup Eero for an undisclosed sum — a hint at Amazon’s future smart home ambitions. The California Department of Motor Vehicles released reports from companies currently testing self-driving cars — fondness Apple, Alphabet’s Waymo, and GM Cruise. Google pledged to spend $13 billion on U.S. datacenters and offices in 24 states this year, and driverless truck startup TuSimple raised $95 million at a $1 billion valuation, joining the ranks of Aurora and Nuro as one of the best-funded companies in the autonomous vehicle industry.

Nearly lost in the shuffle was President Trump’s signing on Monday of an executive order establishing a program — the American AI Initiative — that formalizes several of the proposals made ultimate spring during the White House’s summit on AI. Specifically, it tasks federal agencies with devoting more resources to AI research, training, and promotion and instructs the White House Office of Science and Technology Policy (OSTP), the National Institute of Standards and Technology (NIST), and other departments to draft standards guiding the development of “reliable, robust, trustworthy, secure, portable, and interoperable AI systems” and create AI fellowships and apprenticeships. In the future, these agencies will be required to figure a excellent faith endeavor to provide data, computing resources, and models to AI researchers whenever feasible and to “prioritize AI” investments in their budgets.

Unfortunately, it’s a case of too little, too late.

The U.S. joins many other countries that bear launched national AI guidelines and policies — Australia, Canada, China, Denmark, Finland, France, Germany, India, Japan, Kenya, Malaysia, Mexico, fresh Zealand, Poland, Russia, Singapore, South Korea, Sweden, Taiwan, Tunisia, the United Arab Emirates, and the U.K. Most bear already outstripped — or compass immediate to outstripping — the U.S. with respect to the amount of funding they’ve set aside for AI research.

Canada’s Pan-Canadian simulated Intelligence Strategy, for instance, is a five-year $94 million (CAD $125 million) mode to invest in AI research and talent, complementing the government’s investments of nearly $173 million (CAD $230 million) and $45 million (CAD $230 million) in Scale.AI, a business-led consortium that expects to create immediate to 16,000 jobs. The EU Commission, for its part, has committed to increasing investment in AI from $565 million (€500 million) in 2017 to $1.69 billion (€1.5 billion) by the suspension of 2020. France recently took the wraps off a $1.69 billion (€1.5 billion) initiative aimed at transforming the country into a “global leader” in AI research and training. And South Korea ultimate spring unveiled a multiyear, $1.95 billion (KRW 2.2 trillion) endeavor to strengthen its R&D in AI, with the goal of establishing six AI-focused graduate schools by 2022 and training 5,000 AI specialists.

China’s AI mode is perhaps the most ambitious: In two policy documents, “A Next Generation simulated Intelligence development Plan” and “Three-Year Action mode to Promote the development of New-Generation simulated Intelligence Industry,” the Chinese government laid out its roadmap for cultivating an AI industry worth roughly $147 billion by 2030. The country has already built a $2.1 billion technology park for AI research in Beijing.

Money isn’t the be-all, end-all in AI policy, of course — ethics matter, as evidenced by Amazon, Microsoft, and Google calling for guidelines governing the spend and development of such AI technologies as facial recognition. (All three companies are members of the Partnership for AI, an industry consortium that includes groups sometimes opposed to AI products — fondness Amnesty International and the American Civil Liberties Union.) Unfortunately, the American AI Initiative falls short in this regard, too.

“I’m skeptical that the passing mention of these protections will result is any serious efforts to build in arrogate legal, ethical, and policy safeguards to ensure that AI systems are deployed responsibly,” Professor Kate Crawford, codirector and cofounder of the AI Now Institute at fresh York University, told IEEE Spectrum this week. “We are concerned with the focus on industry at the expense of a broader democratic process and an evidence-led approach to AI policy.”

In contrast to the U.S., the EU Commission has crafted a set of AI guidelines to address ethical issues such as fairness, safety, and transparency and has established the European AI Alliance, a forum for discussion of “all aspects” of AI development and its impacts. Additionally, the body has tasked the High-Level Group on simulated Intelligence — which acts as the steering group for the European AI Alliance — with drafting ethics guidelines.

France likewise plans to develop its own AI regulations and ethics policies, as does Germany. (The latter ultimate year formed a 38-person commission to investigate how machine learning and algorithmic decision-making might disrupt society, and it plans to release a report with recommendations by 2020.) Meanwhile, Singapore’s Advisory Council on the Ethical spend of AI and Data and the U.K.’s Centre for Data Ethics and Innovation bear been tasked with developing a common set of AI ethics standards and frameworks for their respective governments.

The American AI Initiative likewise fails to address issues of multinational collaboration and immigration. That doesn’t compass as a surprise, given the Trump administration’s penniless track record on both fronts.

The Trump administration in February 2018 heightened vetting of H1-B visas, which has led to increased restrictions and rejections of visas and to preferential treatment for holders of advanced degrees from U.S. institutions. (It likewise revoked a guideline that designated “computer programmer” as a protected occupation under the H-1B program.) And the administration delayed implementation of the international entrepreneur rule, or startup visa, which would bear allowed alien entrepreneurs to stay in the U.S. to start a business.

Partly as a result of that and other policy decisions, the number of overseas graduate students in the U.S. fell 5.5 percent in 2017 (from 2016), according to the National Science Foundation. That’s discouraging for organizations fondness the Allen Institute for simulated Intelligence in Seattle, which recently revealed in a Wired editorial that nearly two-thirds of its research scientists hail from countries fondness Egypt, Germany, India, Iran, Israel, Japan, Korea, Norway, the U.K., Taiwan, and Vietnam.

The brain drain has been dramatic. Europe currently leads the world in scholarly output related to AI, according to a report by Elsevier, and China is expected to overtake the EU within the next four years, if current trends continue. India is currently third behind the U.S. and China, while Germany and Japan rank fifth and sixth worldwide in AI research paper output.

“In the name of Buying American and Hiring American [sic], this administration is threatening the intellectual heart of their society, and the consequences of these policies will reverberate throughout their economy,” Allen Institute CEO Oren Etzioni wrote this week. “Providing 10,000 fresh visas for AI specialists, and more for experts in other STEM fields, would revitalize their country’s research ecosystem, empower their country’s innovation economy, and ensure that the United States remains a world superpower in the coming decades.”

This is totality to thunder that the American AI Initiative, as currently proposed, appears poised to underdeliver. And absent a firm timeline for implementation, there’s no guarantee that even its modest proposals will compass to fruition in the foreseeable future.

For AI coverage, route word tips to Khari Johnson and Kyle Wiggers — and be sure to bookmark their AI Channel.

Thanks for reading,

Kyle WiggersAI Staff Writer

P.S. Please Enjoy this talk by Andreessen Horowitz operating ally open Chen about how AI and automation will augmented and enhance humans.

From VB

Jensen Huang, CEO of Nvidia, at CES 2019.

Nvidia’s $2.21 billion in Q4 revenue helps cancel previous stock loss

Nvidia posted earnings that beat Wall Street’s reduced expectations for fourth fiscal quarter earnings for the term ended January 27.

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OpenAI let us try its state-of-the-art NLP text generator

OpenAI’s fresh family of language models achieves state-of-the-art performance on a number of NLP tasks — and sometimes generates convincing original text.

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Amazon reverberate owners can now add their own voice apps to the Alexa Skills Store

Amazon is making voice apps created by reverberate owners with the easy-to-use Skills Blueprint available in the Alexa Skills Store.

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Xnor.ai debuts edge AI that runs on solar power

Xnor.ai today introduced a device capable of running state-of-the-art computer vision algorithms on the edge with a small solar cell and no battery.

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Driverless truck startup TuSimple raises $95 million at $1 billion valuation

China-based autonomous truck startup TuSimple, which has routes in Arizona, raised $95 billion in December 2018 at a $1 billion valuation.

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Project Debater

IBM’s AI takes on world-class debater in dispute about preschool

IBM’s Project Debater engaged in a human versus machine competition before an audience to wrangle for and against subsidies for preschool.

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President Trump will lay out U.S.’ AI plans in an executive order

President Trump will sign an executive order establishing the American AI Initiative, which will lay out the U.S.’ plans for AI research and development.

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Beyond VB

Artificial Intelligence Has create an Unknown ‘Ghost’ progenitor in The Human Genome

Nobody knows who she was, just that she was different: a teenage girl from over 50,000 years ago of such odd uniqueness she looked to be a ‘hybrid’ progenitor to modern humans that scientists had never seen before. (via Science Alert)

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A.I. Shows swear Assisting Physicians

Each year, millions of Americans walk out of a doctor’s office with a misdiagnosis. Physicians try to be systematic when identifying illness and disease, but bias creeps in. Alternatives are overlooked. (via fresh York Times)

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NDP announces $100 million to support Alberta’s simulated intelligence sector

The NDP government has announced plans to spend $100 million over five years to grow the simulated intelligence (AI) sector in Alberta. (via Calgary Herald)

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Google and Microsoft warn that AI might carry out inarticulate things

It’s the not-so-far-away future in San Francisco. One-Wheels and e-scooters litter the road. Your self-driving car has just deposited you at Union Square, and you’ve instructed it to recur in an hour, after you’ve purchased the latest it-smartphone, the iPhone Z. (via Wired)

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UX & Agile: Dream Team or Odd Couple? | killexams.com existent questions and Pass4sure dumps

Are UX specialists satisfied with their experiences in Agile projects? While participating in a recent panel discussion, I asked the audience this question and, judging from a demonstrate of hands, only about half were satisfied. These mixed reviews are consistent with what I’ve heard from UXers in various organizations over the past 10+ years and from what I’ve read in books fondness gaunt UX.

While UX staff sometimes adopt an “us vs. them” perspective, they should start from the position that both UX and Agile bear the selfsame goal — to deliver Great software that delights users. Problems can arise because each community has its own ideas about how to score there. To succeed as a team, these communities need to establish common ground and figure some accommodations: UX staff need to ensure their practices are Agile-friendly and Agile staff need to figure some of their practices a shrimp more UX-friendly. When UX and Agile harmonize their practices, they can convoke the result a Dream Team. And when they don’t, they can convoke the result an Odd pair team.

Let’s discern what a dysfunctional, or Odd Couple, team looks like. Non-UX staff engage in practices such as:

  • keeping UX outside the core team (that is, “us” or “the team” is understood to involve only developers),
  • doing a penniless job applying Agile best practices (for example, writing user stories that don’t effectively articulate the user value), and
  • failing to arrogate project resources (people, money, time) to UX activities fondness user research and design evaluation.
  • For their part, UX staff on an Odd pair team engage in practices such as:

  • working fraction time on multiple projects, rather than being dedicated to a single project,
  • taking a long time to yield intricate design artifacts to hand-off to developers, and
  • treating developers as “them” and not taking an interest in their work beyond UX.
  • This article identifies the topics where UX needs to find common ground with their Agile teammates to figure a Dream Team. We’ll examine collaboration challenges for each of these aspects of UX in turn:

  • Understanding users, that is, conducting user research
  • Large-scale UX design, that is, overall project design direction
  • Small-scale UX design, that is, design in an individual sprint story
  • Evaluating designs
  • UX leaders can spend these topics as a checklist to assess the health of their team and identify areas for improvement.

    Understanding users

    A tenant of UX is to develop a solid understanding of target users as a foundation for design. The quotes below illustrate the inequity between a Dream Team and an Odd pair project:

    The key topics where UX needs to find common ground with Agile are:

  • How much UX research is enough, in the context of limited project resources?
  • How should that UX research be aligned with the project schedule?
  • Generally, UX staff feel that more research is needed than project leaders do, so both parties need to find common ground on how much is enough.

    Given agreement to conduct research, the next point of discussion is how to schedule it vis-a-vis the agile sprint schedule. Models I’ve seen projects spend include:

  • Up front — before project kick-off (Sprint 0)
  • Concurrently with sprints, but outside the sprint schedule
  • Integrated into the sprint schedule
  • The models above are listed in increasing order of logistical difficulty.

    Large-scale UX design

    It’s useful to divide “design” into large-scale vs. small-scale aspects. Here “large scale” design refers to:

  • Project direction, UI architecture, and visionary design concepts
  • Sprint planning and content definition
  • For this aspect of UX, the inequity between success and failure looks fondness this:

    Success from a UX perspective means having a “seat at the table” as one type of project leader and having adequate break to develop and present a vision of the UX to steer the project.

    Common topics of negotiation include:

  • What portion of sprint memoir content (i.e., project resources) will be devoted to delivering UX quality vs. feature quantity?
  • How much is the project team willing to revisit (refine, iterate on) designs from early sprints?
  • How much of the UX team resource will be allocated to big scale design vs. keeping the Agile memoir teams supplied with particular UX designs?
  • How willing is the team to start planning 2–3 sprints ahead so UX can score a head-start?
  • Small-scale UX design

    Here “small-scale” design refers to design to support individual sprint stories. One thing that UX staff thunder they fondness about Agile is its fluid back-and-forth between design and coding, rather than a formal hand-off from a design stage to a coding stage. However, not totality teams bear achieved this example state:

    Aspects that bear to be optimized include:

  • ensuring the user stories clearly articulate the problem being solved in terms apposite to UX,
  • getting developers engaged and collaborating in the UX design work prior to coding, and
  • getting developers being receptive to UX staff providing input and feedback during coding.
  • Evaluating designs

    Another tenant of the UX discipline is the consequence of evaluating designs with users. As with the other aspects of UX, success varies:

    Aspects that bear to be ironed out between UX and the Agile project leads are:

  • In the context of limited project resources, how much design evaluation is enough?
  • What are the expectations for fixing issues?
  • The first challenge is simply getting the break to conduct evaluations. Opportunities can be limited due to staff resources, schedule, or access to users. The second challenge is getting issues fixed. The larger the fix, the harder it is to score it addressed.


    We’ve identified several friction points between the UX and Agile parties in a project team. The more that the UX and Agile staff succeed in finding common ground and making accommodations on these points, the better for everyone — including the users of your software.

    Further reading

    For more quotes and case studies, discern my recent article UX in Agile projects: Taking stock after 12 years.

    For a practical book on this selfsame universal topic, discern gaunt UX.

    For a deep dive on UX research, discern the article Agile development Is No Excuse for Shoddy UX Research.

    For a recent scholarly treatment, discern the edited book Integrating User-Centred Design in Agile Development.

    To better your empathy with software developers, I recommend the book Team Geek: A Software Developer’s steer to Working Well with Others.

    Finally, if you’re looking for something completely different and you’re a history buff, you might fondness the novel The Siege by Ismail Kadare.

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