SDLC and SCRUM for Business Analysts

Classify SDLC models into predictive and adaptive by analyzing the planning phase, order of phases, and customer feedback, and compare models like waterfall, V-model, spiral, and agile.

Explore the waterfall model, the earliest SDLC approach, a sequential lifecycle where each phase finishes before the next begins, including requirements, system design, implementation, integration and testing, deployment, and maintenance.

Describe how the iterative model starts with a small, working increment instead of a complete specification, and expands through repeated cycles prioritizing early feedback and risk management.

Explore the spiral model, a risk-driven software lifecycle that blends iterative and linear phases, with early user involvement and progressive prototyping.

Explore the V-model SDLC, a sequential extension of the waterfall where verification and validation tests align with each development phase from business requirements to coding.

Explore the big bang model, a simple SDLC approach with no defined process that starts with money and effort, delivering high risk software for small projects.

Leverage the rapid application development model to prototype and iteratively build software with early customer feedback. Emphasize reusable components, parallel prototyping, and rapid delivery.

Explore the software prototype model, where prototypes represent functionality and foster early customer feedback, guiding iterative revisions and feasibility decisions within the SDLC.

Explore how the agile mindset addresses uncertainty with iterative development, quick feedback, and readiness for change, emphasizing early software delivery and the twelve principles.

Emphasize individuals and interactions over processes and tools; working software over documentation; customer collaboration over contract negotiation; and responding to change over following a plan, guided by Agile Manifesto principles.

Explore agile practices that implement agile values in software development, including scrum and extreme programming. Learn about test-driven development, Kanban, and continuous integration as complementary approaches.

Explore Scrum as an iterative, incremental agile framework delivering business value through inspect, adapt, and transparency, and trace its origins while sprints produce increments with roles, events, and artefacts.

Identify scrum components: artifacts (product backlog, sprint backlog, increment), roles (product owner, development team, scrum master), and events (planning, daily scrum, sprint review, retrospective), plus ongoing product backlog refinement (grooming).

Define the scrum roles—product owner, development team, and scrum master—and outline how the owner guides vision and release dates, the team delivers a ready increment, and the master removes obstacles.

Discover how a business analyst acts as a proxy product owner, managing backlog and priorities, while the real product owner controls budget and vision.

Explore the three scrum artifacts — product backlog, sprint backlog, and increment — detailing ownership, grooming, the definition of done, and how a fully completed increment delivers value.

Understand the full set of scrum events, from sprint length and goals to planning, daily scrums, sprint reviews, and retrospectives, plus backlog refinement and sprint cancellation rules.

Learn how velocity, the team's completed story points per sprint, and capacity, hours available, inform average historical velocity and future estimates for sprint planning in scrum.

Story points measure task effort as a conditional unit of complexity, risk, and repetition, using a reference task and a Fibonacci scale, with grooming to resolve estimates.

Learn to write requirements as user stories using as a, I want, so that format, with acceptance criteria, given-when-then, and invest principles: independent, negotiable or valuable, evaluable, small, and testable.

Explore essential agile and scrum resources, including the scrum guide and official sites scrum.org, scrum alliance, plus books by Craig Larman, Mike Cohn, Ken Schwaber, Esther Derby, and Diana Larsen.