TANU PAUL

• Completed data cleaning and data validation of existing spreadsheets to promote robust data management platform, resulting in accurate data analysis and entry.
• Provide regular advance analysis for data cleaning and data validation of existing datasets into data management platform, resulting in accurate data analysis and entry.
• Writing new SQL scripts & maintaining the regular ones for extracting data from provided Data warehouse for finance transactions, Appointment data, Schedule datasets, raised Incident’s order, etc.
• Collaborate with stakeholders to identify business requirements and support tailor analysis approach for solutions.
• Implement data wrangling to the discovered sources dataset with quality check, data-cleaning, and transforming structured set into publishable data model.
• Analyzed data to identify root causes of problems and recommend corrective actions.
• Commission new and decommission archived data sets under mentor supervision into cloud archive.

• Engage in independent study and research to deepen understanding of course materials and explore recently used analytical tools and technologies.
• Take advantage of opportunities for internships, co-op programs, or work-study placements in various organizations during study relevant to academic and career interests.
• Actively engage with the university technology development community by attending events, seminars, workshops, and networking opportunities.
• Complete assigned coursework, including readings, assignments, projects, and exams, within specified deadlines.

• Developed strong professional relationships with faculty members by actively participating in departmental meetings and events.
• Compiled annotated bibliographies on relevant topics to facilitate future reference for colleagues'' ongoing projects.

• Streamlined data analysis workflows for increased efficiency and faster decision-making processes.
• Improved data accuracy by implementing stringent data validation processes and quality control measures.
• Surveyed clients to ascertain requirements and expectations for product.
• Developed complex dashboard and reporting tools to track business performance metrics.
• Delivered analysis of market, sales and consumer trend impact on long and short-term strategies.
• Collaborated with stakeholders to identify business needs and data sources.
• Analyzed open orders, backlog, and operation data to provide operation team with insights.
• Streamlined data analysis workflows for increased efficiency and faster decision-making processes.
• Reduced manual data entry errors by designing and deploying automated ETL processes to transform raw data into usable formats.
• Enabled accurate trend analysis through meticulous data cleansing and standardization procedures.