Difference between revisions of "Requirements Management"
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| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
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| − | [https://www.youtube.com/results?search_query=Requirements+management | + | [https://www.youtube.com/results?search_query=ai+Requirements+management YouTube] |
| − | [https://www.google.com/search?q=Requirements+management+ | + | [https://www.quora.com/search?q=ai%20Requirements%20management ... Quora] |
| + | [https://www.google.com/search?q=ai+Requirements+management ...Google search] | ||
| + | [https://news.google.com/search?q=ai+Requirements+management ...Google News] | ||
| + | [https://www.bing.com/news/search?q=ai+Requirements+management&qft=interval%3d%228%22 ...Bing News] | ||
| − | * [[ | + | * [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]] |
| − | * | + | * [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]] |
| − | ** | + | * [[Architectures]] for AI ... [[Generative AI Stack]] ... [[Enterprise Architecture (EA)]] ... [[Enterprise Portfolio Management (EPM)]] ... [[Architecture and Interior Design]] |
| − | + | * [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]] | |
| − | * [[Strategy & Tactics | + | * [[Risk, Compliance and Regulation]] ... [[Ethics]] ... [[Privacy]] ... [[Law]] ... [[AI Governance]] ... [[AI Verification and Validation]] |
| − | * [[AI | + | * [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]] |
| − | * [[ | + | * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]] |
| − | * [[ | + | * [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]] |
| − | * [[ | + | * [[Prompt Engineering (PE)]] ... [[Prompt Engineering (PE)#PromptBase|PromptBase]] ... [[Prompt Injection Attack]] |
| − | * [[ | + | * [[Python]] ... [[Generative AI with Python|GenAI w/ Python]] ... [[JavaScript]] ... [[Generative AI with JavaScript|GenAI w/ JavaScript]] ... [[TensorFlow]] ... [[PyTorch]] |
| − | * [[Assistants]] ... [[ | + | * [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games - Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]] ... [[Game Design | Design]] |
| − | * [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] | + | * [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]] |
| − | * [[Attention]] Mechanism ...[[Transformer]] | + | * [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]] |
| + | * [[Attention]] Mechanism ...[[Transformer]] ...[[Generative Pre-trained Transformer (GPT)]] ... [[Generative Adversarial Network (GAN)|GAN]] ... [[Bidirectional Encoder Representations from Transformers (BERT)|BERT]] | ||
* [https://adtmag.com/pages/topic-pages/ai.aspx Application Development Trends - ADTmag] | * [https://adtmag.com/pages/topic-pages/ai.aspx Application Development Trends - ADTmag] | ||
* [https://apps.dtic.mil/dtic/tr/fulltext/u2/1053222.pdf Artificial Intelligence: The Bumpy Path Through Defense Acquisition | Eric J. Ehn] | * [https://apps.dtic.mil/dtic/tr/fulltext/u2/1053222.pdf Artificial Intelligence: The Bumpy Path Through Defense Acquisition | Eric J. Ehn] | ||
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* [[Defense]]: [https://acqnotes.com/acqnote/tasks/requirements-development-overview Requirements Development] | [https://acqnotes.com DOD AcqNotes] | * [[Defense]]: [https://acqnotes.com/acqnote/tasks/requirements-development-overview Requirements Development] | [https://acqnotes.com DOD AcqNotes] | ||
* [https://thebrazilianba.com/2023/01/24/chat-gpt-as-a-tool-for-business-analysis/ The Brazilian Business Analysis] | * [https://thebrazilianba.com/2023/01/24/chat-gpt-as-a-tool-for-business-analysis/ The Brazilian Business Analysis] | ||
| + | * [https://www.xenonstack.com/blog/ai-in-requirement-management AI in Requirements Management | Benefits and its Processes | Jagreet Kaur - XENONSTACK] | ||
| − | <hr> | + | <hr><center><b> |
| − | Being semi-structured, requirements led themselves to [[Natural Language Processing (NLP)]] nicely | + | Being semi-structured, requirements led themselves to [[Natural Language Processing (NLP)]] nicely |
| − | <hr> | + | </b></center><hr> |
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"Will AI take over the Business Analyst role?" and "How do we stay relevant in a rapidly changing landscape?" | "Will AI take over the Business Analyst role?" and "How do we stay relevant in a rapidly changing landscape?" | ||
| − | The process Deirdre explained during the webinar was based on "The Knowledge Brief" part 7. However, she emphasized that understanding the previous six parts is crucial since they provide context for the organization's needs. Without this context, businesses can't harness the full potential of AI technology. Deirdre also discussed the potential role of AI in business analysis. While AI can provide insight into information, it lacks the creativity and context of human problem-solving abilities. Attendees agreed that business analysts could still play a crucial role in utilizing AI tools for data analysis and using their intuition and experience to stay relevant in the fast-changing world. By combining business analysis practices with AI technology, business analysts can improve project outcomes. The webinar was informative and motivating, encouraging attendees to keep up with technological advancements and understand their advantages and limitations. Deirdre's insights based on "The Knowledge Brief" part 7 highlighted the importance of context and its significant impact on the successful use of AI technology in business analysis. | + | The process Deirdre explained during the webinar was based on "The Knowledge Brief" part 7. However, she emphasized that understanding the previous six parts is crucial since they provide [[context]] for the organization's needs. Without this [[context]], businesses can't harness the full potential of AI technology. Deirdre also discussed the potential role of AI in business analysis. While AI can provide insight into information, it lacks the creativity and [[context]] of human problem-solving abilities. Attendees agreed that business analysts could still play a crucial role in utilizing AI tools for data analysis and using their intuition and experience to stay relevant in the fast-changing world. By combining business analysis practices with AI technology, business analysts can improve project outcomes. The webinar was informative and motivating, encouraging attendees to keep up with technological advancements and understand their advantages and limitations. Deirdre's insights based on "The Knowledge Brief" part 7 highlighted the importance of [[context]] and its significant impact on the successful use of AI technology in business analysis. |
Here are the 5 tips for business analysts that come from this session: | Here are the 5 tips for business analysts that come from this session: | ||
| − | * Understand the "The Knowledge Brief®" parts 1-6 to provide context for your organization's needs. | + | * Understand the "The Knowledge Brief®" parts 1-6 to provide [[context]] for your organization's needs. |
* Develop a solid understanding of the business analysis profession through certification and training. | * Develop a solid understanding of the business analysis profession through certification and training. | ||
* Use AI as a supplement to your skills, not as a replacement. | * Use AI as a supplement to your skills, not as a replacement. | ||
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| − | <youtube> | + | <youtube>b9Y2IfrDLeQ</youtube> |
| − | <b>Analysis | + | <b>How to Use [[ChatGPT]] as a Business Analyst | AI and Business Analysis |
| − | </b><br> | + | </b><br>In this video, I’ll show you how to use [[ChatGPT]] for business analysis work. Specifically, I’ll be asking the AI bot to draft me a use case for combining accounts. You’ll see that the bot can do a really great job at providing you a starting point, but you’ll still need to be mindful of and incorporate your business rules, goals, and other important factors to ensure that the final output aligns with the organization's objectives. If you’re looking to stay ahead of the curve, I encourage you to incorporate [[ChatGPT]] into your BA workflow. |
| + | |||
| + | Claim your use case template here: http://bit.ly/3YSqpSK | ||
| + | |||
| + | Learn about the Requirements Discovery Checklist Pack here: http://bit.ly/41fKKD2 | ||
| + | |||
| + | Sign up for a free workshop to kickstart your success as a BA: https://bit.ly/3SzmF5c | ||
| + | |||
| + | Watch my video on how to write a use case here: https://bit.ly/3xM1jJj | ||
| + | |||
| + | Connect with us on: Website: https://bit.ly/3EfMmnm | ||
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<youtube>3z00DJtpT74</youtube> | <youtube>3z00DJtpT74</youtube> | ||
<b>Impact of AI on Business Analysis with Author Paolo Sammicheli | <b>Impact of AI on Business Analysis with Author Paolo Sammicheli | ||
| − | </b><br>In this episode, Paolo talks about the demand for Business Analysts in a world of AI. The purchase or read Paolo's book go here: https://paolo.sammiche.li/ About Paolo: Paolo Sammicheli is an Italian entrepreneur, International Speaker, and Author of the books "Scrum for Hardware," the first significant publication in the world on the topic, and "Scrum in AI - Artificial Intelligence Agile Development with Scrum and MLOps," with the foreword by Jeff Sutherland, co-author of Scrum and the Agile Manifesto. Today Paolo works as an Agile Business Coach, specialized in Scrum, Scrum@Scale, Kanban, Design Thinking, and Lean Startup, helping organizations uncover better ways to delight their customers. Scrum and Scrum@Scale Trainer for Scrum Inc, Lean-Agile Procurement Trainer, and Management 3.0 Facilitator. Executive Certificate in Management and Leadership from MIT Sloan School of Business. Link to purchase the foundational template: https://baknowledgeshare.com/downloads/business-analysis-foundational-templates/ Visit our website at https://baknowledgeshare.com/downloads/cbap-ccba-ecba-key-term-flashcards/ to purchase flashcards for business analysis key terms. Thank you for visiting this channel. Do consider subscribing to this channel to get notified of updates. Blog: https://baknowledgeshare.wordpress.com/ | + | </b><br>In this episode, Paolo talks about the demand for Business Analysts in a world of AI. The purchase or read Paolo's book go here: https://paolo.sammiche.li/ About Paolo: Paolo Sammicheli is an Italian entrepreneur, International Speaker, and Author of the books "Scrum for Hardware," the first significant publication in the world on the topic, and "Scrum in AI - Artificial Intelligence Agile [[Development]] with Scrum and MLOps," with the foreword by Jeff Sutherland, co-author of Scrum and the Agile Manifesto. Today Paolo works as an Agile Business Coach, specialized in Scrum, Scrum@Scale, Kanban, Design Thinking, and Lean Startup, helping organizations uncover better ways to delight their customers. Scrum and Scrum@Scale Trainer for Scrum Inc, Lean-Agile Procurement Trainer, and Management 3.0 Facilitator. Executive Certificate in Management and Leadership from MIT Sloan School of Business. Link to purchase the foundational template: https://baknowledgeshare.com/downloads/business-analysis-foundational-templates/ Visit our website at https://baknowledgeshare.com/downloads/cbap-ccba-ecba-key-term-flashcards/ to purchase flashcards for business analysis key terms. Thank you for visiting this channel. Do consider subscribing to this channel to get notified of updates. Blog: https://baknowledgeshare.wordpress.com/ |
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<youtube>aB0tnT36UaI</youtube> | <youtube>aB0tnT36UaI</youtube> | ||
<b>Applying Machine Learning Techniques to the Flexible Assessment of Requirements Quality | <b>Applying Machine Learning Techniques to the Flexible Assessment of Requirements Quality | ||
| − | </b><br>In the world of systems engineering, the importance of having high quality requirements is well known and that is why there are standards and guidelines that establish the characteristics that the requirements must have for considering them of good quality. To obtain quality measurements of the requirements it is common to use quantitative quality metrics based on established standards. However, the risk is to build assessment methods and tools that are both arbitrary and rigid in the parameterization and combination of metrics. This webinar is focused on the presentation of a flexible method to assess and improve the quality of requirements that can be easily adapted to different | + | </b><br>In the world of systems engineering, the importance of having high quality requirements is well known and that is why there are standards and guidelines that establish the characteristics that the requirements must have for considering them of good quality. To obtain quality measurements of the requirements it is common to use quantitative quality metrics based on established standards. However, the risk is to build assessment methods and tools that are both arbitrary and rigid in the parameterization and combination of metrics. This webinar is focused on the presentation of a flexible method to assess and improve the quality of requirements that can be easily adapted to different [[context]]s, projects, organizations and quality standards, with a high degree of automation. In the method proposed, the domain experts contribute with an initial set of requirements that they have classified according to their quality, and their quality metrics are extracted. Then machine learning techniques are used to emulate the implicit expert’s quality function. A procedure to suggest least-effort improvements in bad requirements is also provided. The method is easily tailorable to different [[context]]s, different styles to write requirements, and different demands in quality. The whole process of inferring and applying the quality rules adapted to each organization is highly automated. |
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| + | <youtube>eu6pT-eNi-s</youtube> | ||
| + | <b>Analysis of Software Requirements with Natural Language Processing | ||
| + | </b><br>Prof. Lionel Briand University of Luxembourg, Luxembourg Huawei Workshop on Applications of Artificial Intelligence to Software Engineering December 15th 2017 | ||
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| + | <youtube>TgAEJki-lTs</youtube> | ||
| + | <b>Domain Knowlege Using [[OpenAI]] [[ChatGPT]] (as a Business Analyst) | ||
| + | </b><br>[[OpenAI]]s [[ChatGPT]] is a complete game-changer for business analysts. In this live session, we used this tool to quickly learn about Salesforce, the sales domain, and the insurance domain. | ||
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= Requirements Management Tools = | = Requirements Management Tools = | ||
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<youtube>bixIrCKirQA</youtube> | <youtube>bixIrCKirQA</youtube> | ||
<b>Requirements Traceability with Jira | <b>Requirements Traceability with Jira | ||
| − | </b><br>The Atlassian Ecosystem (customers, partners & app vendors) frequently come up with very interesting and creative ways to overcome tough Software Development Lifecycle (SDLC) challenges. In our September webinar, our special guests, Erez Marcovich from Amdocs and Yaniv Shoshani from Methoda will share their expertise on how they together tackled Amdocs’ Requirements Traceability challenges using Jira, Structure, and Xray. To learn how to integrate Xray with Structure for Jira: https://bit.ly/2L7Fn2K To learn more about Xray: https://www.getxray.app/ To learn more about Methoda: https://www.methoda.co.il/en/ To learn more about Amdocs: https://www.amdocs.com To try out Structure for Jira: https://alm.works/structure-amdocs | + | </b><br>The Atlassian Ecosystem (customers, partners & app vendors) frequently come up with very interesting and creative ways to overcome tough Software [[Development]] Lifecycle (SDLC) challenges. In our September webinar, our special guests, Erez Marcovich from Amdocs and Yaniv Shoshani from Methoda will share their expertise on how they together tackled Amdocs’ Requirements Traceability challenges using Jira, Structure, and Xray. To learn how to integrate Xray with Structure for Jira: https://bit.ly/2L7Fn2K To learn more about Xray: https://www.getxray.app/ To learn more about Methoda: https://www.methoda.co.il/en/ To learn more about Amdocs: https://www.amdocs.com To try out Structure for Jira: https://alm.works/structure-amdocs |
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* [https://www.wordtemplatesonline.net/requirements-analysis-template/ 20+ Requirements Analysis Templates & Examples | Word Templates Onine] | * [https://www.wordtemplatesonline.net/requirements-analysis-template/ 20+ Requirements Analysis Templates & Examples | Word Templates Onine] | ||
* [https://www.fp7-adventure.eu/wp-content/uploads/2012/04/D2.3_Requirement-Analysis-Report_v1.0_final.pdf Requirements Analysis Report | UVI, INESC, TUDA, UVA (lead), TANet, AZEV, ABB] ...Adventure: The Plug-and-Play Virtual Factory | * [https://www.fp7-adventure.eu/wp-content/uploads/2012/04/D2.3_Requirement-Analysis-Report_v1.0_final.pdf Requirements Analysis Report | UVI, INESC, TUDA, UVA (lead), TANet, AZEV, ABB] ...Adventure: The Plug-and-Play Virtual Factory | ||
| − | * [https://dl.icdst.org/pdfs/files/f9c7c841bf3dbeb523ec2b51f1cd5bc1.pdf User Requirements Analysis Report | D M Sergeant, S Andrews, and A Farquhar] ...Embedding a VRE | + | * [https://dl.icdst.org/pdfs/files/f9c7c841bf3dbeb523ec2b51f1cd5bc1.pdf User Requirements Analysis Report | D M Sergeant, S Andrews, and A Farquhar] ...[[Embedding]] a VRE |
= The Expert = | = The Expert = | ||
Latest revision as of 13:03, 6 November 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Analytics ... Visualization ... Graphical Tools ... Diagrams & Business Analysis ... Requirements ... Loop ... Bayes ... Network Pattern
- Strategy & Tactics ... Project Management ... Best Practices ... Checklists ... Project Check-in ... Evaluation ... Measures
- Architectures for AI ... Generative AI Stack ... Enterprise Architecture (EA) ... Enterprise Portfolio Management (EPM) ... Architecture and Interior Design
- Development ... Notebooks ... AI Pair Programming ... Codeless ... Hugging Face ... AIOps/MLOps ... AIaaS/MLaaS
- Risk, Compliance and Regulation ... Ethics ... Privacy ... Law ... AI Governance ... AI Verification and Validation
- Strategy & Tactics ... Project Management ... Best Practices ... Checklists ... Project Check-in ... Evaluation ... Measures
- Artificial Intelligence (AI) ... Generative AI ... Machine Learning (ML) ... Deep Learning ... Neural Network ... Reinforcement ... Learning Techniques
- Conversational AI ... ChatGPT | OpenAI ... Bing/Copilot | Microsoft ... Gemini | Google ... Claude | Anthropic ... Perplexity ... You ... phind ... Ernie | Baidu
- Prompt Engineering (PE) ... PromptBase ... Prompt Injection Attack
- Python ... GenAI w/ Python ... JavaScript ... GenAI w/ JavaScript ... TensorFlow ... PyTorch
- Gaming ... Game-Based Learning (GBL) ... Security ... Generative AI ... Games - Metaverse ... Quantum ... Game Theory ... Design
- Agents ... Robotic Process Automation ... Assistants ... Personal Companions ... Productivity ... Email ... Negotiation ... LangChain
- Large Language Model (LLM) ... Natural Language Processing (NLP) ...Generation ... Classification ... Understanding ... Translation ... Tools & Services
- Attention Mechanism ...Transformer ...Generative Pre-trained Transformer (GPT) ... GAN ... BERT
- Application Development Trends - ADTmag
- Artificial Intelligence: The Bumpy Path Through Defense Acquisition | Eric J. Ehn
- AI driven requirements management ...IBM Engineering Lifecycle Management (ELM) | IBM
- Tools & Trends in Requirements Engineering | Hubert Spieß
- Why Agile Methodologies Miss The Mark For AI & ML Projects | Kathleen Walch - Forbes
- Managing workflow of customer requirements using machine learning | A. Lyutov, Y. Uyguna, and M. Thorsten Hütt - ScienceDirect
- reQlab | IT-Designers ...a state-of-the-art artificial intelligence tool improving natural language requirements. With its integration in Polarion, it can be used during the normal process of writing your requirements.
- Requirements Modeling Technology: A Vision For Better, Faster, And Cheaper Systems | Darrell Barker
- RE4AI ...motivating cross fertilization between AI and Requirements Engineering (RE)
- Defense: Requirements Development | DOD AcqNotes
- The Brazilian Business Analysis
- AI in Requirements Management | Benefits and its Processes | Jagreet Kaur - XENONSTACK
Being semi-structured, requirements led themselves to Natural Language Processing (NLP) nicely
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Requirements Management Tools
- The Best Requirements Management Tools Of 2020 | Ben Aston - dpm
- Artificial Intelligence & The Future Of Project Management (With Dennis Kayser From Forecast) | Ben Aston - dpm
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Discipline
(testable, cohesive, complete, consistent, atomic, traceable, unambiguous, prioritized, and solution-agnostic):
- 20+ Requirements Analysis Templates & Examples | Word Templates Onine
- Requirements Analysis Report | UVI, INESC, TUDA, UVA (lead), TANet, AZEV, ABB ...Adventure: The Plug-and-Play Virtual Factory
- User Requirements Analysis Report | D M Sergeant, S Andrews, and A Farquhar ...Embedding a VRE
The Expert
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