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Introduction to Agile UN Big Data 2016
The document discusses the principles of Agile methodologies, particularly in the context of big data and software development. It contrasts Agile with traditional Waterfall approaches and emphasizes the importance of iterative processes, continuous improvement, and effective communication. Key frameworks like Scrum and Kanban are briefly introduced, along with the importance of focusing on delivering business value and user-centered results.
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Introduction to Agile UN Big Data 2016
- 1. Introduction to Agile InternationalConference on Big Data for Official Statistics Dublin 2016
- 2. Simon Reindl Professional ScrumTrainer with Scrum.Org EBMgt Engagement Manger, Coach, Trainer, Consultant, Speaker @s_reindl uk.linkedin.com/in/simonreindl Simon.Reindl@advancedproductdelivery.com
- 3. Has this happenedto your project? © Advanced Product Delivery Limited 2016 3
- 4. Insanity: doing the samething over and over again and expecting different results. Albert Einstein
- 5. 5 Process Complexity Requirements TechnologyClose to Certain Farfrom Certain Close to Agreement Far from Agreement Simple Complex Anarchy Emergent Understanding
- 6. A different (scientific)approach •Iterative •Incremental •Fast Feedback •Frequent checks with the consumer (user) •Focus on solving the problem, not documenting it
- 7. Agility Definition of agile adjective •able to move quickly and easily adverb • agility from Latin agilis - 'do‘ Quickly and deliberately respond to change while managing risk 7 Yoda
- 8.
- 9. Agile is amindset
- 10. The CHAOS Manifesto(2015) 10https://www.infoq.com/articles/standish-chaos-2015 11% 60% 29% Waterfall Successful Challenged Failed 39% 52% 9% Agile Successful Challenged Failed
- 11. Agile Frameworks share3 pillars 11 Inspection
- 12. Act on theFeedback •Measure •Understand •Act
- 13.
- 14. Lean Principles Customer Value Respectand engage the people Improve Flow Eliminate waste Pull not Push Continuous Improvement See the whole 14 Lean Define Measure Analyse Improve Control Kaizen
- 15. Agile Manifesto… … wehave come to value: Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan http://www.agilemanifesto.org/ 15
- 16. 16 Frameworks Overview Plan Driven Predictive Prince2 PMBOK CMMI Value Driven Empirical Scrum XP Kanban Iterative
- 17. Range of AgileFrameworks 17 Prescriptive Adaptive RUP 120+ XP 12 Scrum 11 Kanban 3 None 0 Subtractive Additive DSDM
- 18. Focus is onDelivering Business Value • Adaptive to demands of the Business • Put the business in the Driving Seat • Business own the “What” • IT own the “How” • Focus on delivering a working product 18 What How Product
- 19. However beautiful the strategy,you should occasionally look at the results. Winston Churchill
- 20. Focus on flow 20©Advanced Product Delivery Limited 2016
- 21. Kanban (Signal Flow) •Visualise the work • Limit Work In Progress • Measure and Manage flow • Make process and policies explicit • Implement Feedback loops • Improve collaboratively, evolve experimentally 21
- 22. Flow - 2main metrics Lead Time •The time from concept to customer •Can be measured across lanes Cycle Time •How frequently your product is finished Do you know this for your products? Would it help ? 22© Advanced Product Delivery Limited 2016
- 23. XP (eXtreme Programming Comesfrom an engineering perspective •Simplicity •Communication •Feedback •Respect •Courage 23
- 24. Scrum is … •Anframework for Agile software development •A set of rules defined in the Scrum Guide •Easy to learn but difficult to master
- 25. 25© Advanced ProductDelivery Limited 2016
- 26.
- 27. The Product BacklogIceberg Other stories waiting to be worked on. Not refined yet. 1-3 Sprints Order Release Story Theme Epic © Advanced Product Delivery Limited 2016 27
- 28. Working with BigData •Data is Different •But not that much! •How to implement Agility with Big Data …
- 29. Key aspects •Team Practices– Communicate •Iterative, Incremental – “Chunking” •Focus on user visible Value •Be “Done” •Document continuously •Test and deploy automatically •Bring the end users closer - Collaborate
- 30. “Done” with BigData •Built/Coded •Tested at volume •Deployed •Rollback tested •Performance tested •Security tested
- 32.