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Ramya .C
Ramya .C

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Day 19 of My Data Analytics Journey !

Today’s session was a special class on Software Testing where I explored different software development models and Agile practices. These concepts are important because they define how teams plan, build, and deliver software.


📌 Software Development Models I Learned

  • Waterfall Model – A linear and sequential model where each phase (requirements, design, implementation, testing, deployment) must be completed before moving to the next.
  • Pilot Model – A small-scale implementation before the full system rollout, used to validate feasibility.
  • Spiral Model – Combines iterative development with risk analysis, emphasizing continuous refinement.

📌 Agile Framework Concepts

  • Sprint – A short, time-boxed period where a set of work is completed.
  • Epic – A large body of work that can be broken down into multiple sprints or user stories.
  • Agile Methodology – An iterative and flexible approach where software is built in small increments with constant feedback.

📌 Agile Meeting Types

  • Stand-up Meeting – A short daily meeting to discuss progress, blockers, and plans.
  • Product Planning – Defines vision, goals, and backlog for the product.
  • Sprint Planning – Decides what work will be completed in the next sprint.
  • Sprint Demo Meeting – Showcases the work completed during the sprint.
  • Sprint Retrospective – A review meeting to reflect on what went well and what can be improved.

📌 Key Terms

  • Shippable Product – A working software increment delivered at the end of each sprint that adds value to the user.
  • Retro – Short form for retrospective, a meeting to continuously improve team performance.

🔍 Reflection

Learning about development models and Agile practices helped me understand how software is delivered efficiently in the real world. These models are not just for testing but also shape how analytics projects can be planned and executed.

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