BA-111IT Business Analysis Programı

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Business analysis as a discipline; Business Analyst, System Analyst, Product Owner, Product Manager and Project Manager; business needs, stakeholders, change, solutions, context and value; SDLC and PDLC; project versus product thinking; waterfall, iterative, Agile, Lean and hybrid delivery

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Business-analysis context map and role comparison.

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Problem and opportunity statements; current-state and future-state analysis; root-cause analysis with Five Whys and Fishbone Diagram; business goals and strategic alignment; assumptions, constraints, risks and dependencies; solution options; business cases, KPIs, benefits and change strategy

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Opportunity brief, root-cause model and lightweight business case.

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Stakeholder identification and mapping; power, interest, influence and impact; RACI; elicitation planning; interviews, workshops, observation, surveys and document analysis; personas and empathy maps; communication planning; negotiation and conflict management; remote and inclusive facilitation

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Stakeholder map, elicitation plan, interview guide and workshop findings.

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Business, stakeholder, solution and transition requirements; functional and non-functional requirements; requirement quality and SMART objectives; business rules; assumptions and constraints; CRUD and functional decomposition; MoSCoW, RICE, WSJF, Kano and value-versus-effort; traceability, versioning, change impact, verification, validation and approval; BRD, SRS, FRD, NFRD, PRD and fit-for-purpose documentation

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Requirements catalogue, prioritisation model, traceability matrix and change assessment.

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Process discovery and scope; process maps versus process models; SIPOC; AS-IS and TO-BE analysis; BPMN 2.0.2 events, activities, gateways, pools, lanes and message flows; data, subprocesses, exceptions and boundary events; synchronous and asynchronous processes; process KPIs; business rules and DMN introduction; process improvement and re-engineering

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AS-IS and TO-BE BPMN models, business rules and improvement brief.

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System-context diagrams; use case diagrams and specifications; activity, sequence and state-machine diagrams; domain and conceptual class models; data-flow diagrams; interface analysis; wireframes and low fidelity prototypes; consistency between requirements and models

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Complete solution-model set for a digital service.

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Agile values and principles; Scrum accountabilities, events and artefacts; Product Goal, Sprint Goal and Definition of Done; Product Backlog management and refinement; user stories and INVEST; story splitting; Gherkin acceptance criteria; estimation and story points; Kanban, WIP, lead time, cycle time and throughput; continuous discovery and delivery

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Product Goal, prioritised backlog, user stories, acceptance criteria and story map.

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Product Manager, Product Owner, BA and Project Manager; product vision, strategy, goals and OKRs; market and competitor analysis; Jobs to Be Done; customer interviews, personas and journey maps; problem statements, assumptions and hypotheses; opportunity mapping and continuous discovery; Value Proposition and Business Model Canvas; RICE, WSJF, Kano and value-versus-effort; MVP, MLP, MMF and story mapping; outcome-based and Now–Next–Later roadmaps; North Star Metric, metric trees, funnels, conversion and retention; experiments, A/B testing, go-to-market and product lifecycle

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Product strategy, MVP, roadmap, metrics tree and experiment brief.

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Conceptual, logical, physical data models; entities, attributes, keys, relationships, cardinality; normalisation, ERD; data dictionaries, quality, ownership, lineage, privacy; SELECT, WHERE, ORDER BY, NULL, CASE; JOIN, GROUP BY, HAVING, aggregations; subqueries, CTEs; window functions; business research questions; dashboards, data visualisation

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ERD, data dictionary, SQL analysis, findings and dashboard specification.

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HTTP, REST, SOAP, GraphQL, gRPC concepts; JSON, XML; synchronous and asynchronous communication; webhooks, event-driven integrations; OpenAPI, AsyncAPI; requests, responses, headers, parameters, error codes; authentication, authorisation, OAuth 2.0, OpenID Connect; idempotency, pagination, filtering, rate limits, versioning; API documentation, mocking, contract testing; Postman

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Sequence diagram, API requirements, OpenAPI contract and Postman collection.

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Client-server and web architecture; monoliths, modular monoliths, microservices; microfrontends overview; cloud, containers, serverless; caching, load balancing; scalability, availability, reliability, resilience; data consistency; Kafka, RabbitMQ, queues, event-driven architecture; logs, metrics, tracing, observability; authentication, authorisation, RBAC, ABAC; security, privacy, accessibility, performance, maintainability; architecture diagramming, TOGAF overview

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Architecture diagram, integration map, NFR catalogue and security checklist.

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BA responsibilities in testing; equivalence partitioning; boundary-value analysis; decision-table, state-transition testing; scenario, use-case, exploratory, API, performance, accessibility testing; test plans, test data; defects, severity, priority, triage; requirements-to-test traceability; UAT planning, execution; DEV, TEST, UAT, staging, production; release readiness, CI/CD; post-launch monitoring; solution performance, benefits realisation

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Test strategy, UAT plan, traceability matrix, release checklist and evaluation plan.

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Automation, RPA, AI differences; automation-candidate selection; process stability, volume, rules, exceptions, data quality; feasibility, ROI; human-in-the-loop processes; bot requirements; security, audit trails, exception handling, monitoring; process mining, task mining; UiPath, Power Automate, AI Builder overview; automation governance

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Automation assessment, TO-BE process, bot requirements and control matrix.

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Generative-AI capabilities, limitations; prompt and context design; structured outputs; research, document analysis; interview synthesis; requirements, user stories, acceptance criteria; AI-assisted BPMN, UML, testing, SQL, API analysis; repeatable AI workflows, agent concepts; source verification, hallucination detection; confidentiality, privacy, intellectual property, prompt injection; human accountability, AI validation logs

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AI-assisted BA package, validation checklist, correction log and AI-use declaration.

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AI use-case qualification; business value, data readiness; deterministic versus probabilistic requirements; accuracy, hallucination, latency, cost; evaluation datasets, acceptance thresholds; human oversight, escalation, fallback; bias, explainability, privacy, intellectual property; RAG, AI agents, tool-calling; NIST AI Risk Management Framework; monitoring, feedback, drift, AI incidents

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AI product requirements, evaluation plan, oversight model and AI risk register.

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Realistic digital-product challenge; business case, stakeholder discovery; AS-IS and TO-BE processes; product vision, MVP, roadmap; requirements, traceability; data, UML, architecture models; API contract; testing, UAT; release and measurement plan; mid-project change request; team presentation, individual defence

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Complete end-to-end BA, SA, product and AI portfolio.