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Business Analyst as Data/Report | Gaining substantial experience | Retail Industry1. Requirements Gathering and Stakeholder Workshops:- Collaborate with business stakeholders to explore and capture detailed requirements for report creation.- Organize exchange workshops to gain insights into the problem to be solved. Engage with stakeholders to understand their needs thoroughly.2. User Stories and Problem Resolution:- Identify user stories related to report completion. These stories represent specific tasks that need resolution.Ensure that each user story aligns with the overall report objectives.3. System Understanding and Optimal Solutions:- Deeply understand the system architecture and data flow. This knowledge is crucial for proposing effective solutions.- Find optimal solutions that address business users’ tasks. Consider efficiency, accuracy, and usability.4. Collaboration with Data Engineers:- Work closely with data engineers to propose and implement solutions.- Leverage expertise to design data flow and processing rules that enhance report quality.5. Report Templates and Documentation:- Build well-structured report templates. Ensure consistency in formatting and layout.- Define data processing rules within the report, if applicable.- Document the rationale behind design decisions and any relevant information related to the reports.6. Data Flow and Documentation:- Draw clear data flow diagrams. Visualize how data moves through the system and report components.- Write comprehensive documents that explain the purpose, functionality, and usage of each report.- Store these documents for easy reference and knowledge sharing.7. Testing and Error Correction:- Test report data in different environments (CI, UAT, and PROD).

Business Analyst as AI/ML intiatives | Banking Industry- Conduct comprehensive reviews and analyses of current and proposed business operations, utilizing AI/ML tools.- Identify opportunities for improvement and devise AI/ML-based solutions to address business challenges.- Facilitate effective communication with key stakeholders, translating data insights into actionable strategies.- Collaborate with project managers and cross-functional teams to define configuration specifications.- Perform quality assurance, define reporting requirements, and optimize integration.- Communicate key findings to the product team, driving continuous improvement.- Assisted in the design, documentation, and maintenance of AI/ML system processes indicates a holistic approach.