What I Offer:As a Data Analyst Mentor, I provide personalized guidance and support to help individuals excel in their data analysis journey. My approach blends technical expertise with practical insights to equip mentees with the skills and confidence needed to tackle real-world challenges. Whether it's mastering analytical tools, refining problem-solving abilities, or navigating career paths, I'm committed to fostering growth every step of the way.Key Responsibilities:- Conduct one-on-one mentoring sessions to assess mentees' skills, goals, and areas for improvement.- Develop customized learning plans tailored to each mentee's needs and learning style.- Provide hands-on support in data analysis techniques, including data wrangling, statistical analysis, and machine learning.- Offer constructive feedback on projects, assignments, and portfolio development to enhance mentees' proficiency and marketability.- Share industry insights, best practices, and resources to help mentees stay abreast of the latest trends and advancements in data analysis.- Foster a supportive and collaborative learning environment where mentees feel empowered to explore, experiment, and grow.

Domain: FinanceRole: Data AnalystData Skillset: SQL, Oracle, DAX, SSIS, SSAS, Python (Pandas, Numpy, Seaborn, mathplotlib), SeleniumData Toolset: Microsoft Excel, Microsoft Power BI, Microsoft SQL Server, SQL Developer, Microsoft Visual Studio, Visual Studio Code, Paginated ReportData Mindset: Design and Build Datawarehouse, EDA, SWOTProject Management Framework: Scrum, AgileRole Description:• Managed extensive data processing across Oracle, SQL Server, and Excel to establish robust Data Warehouses, optimizing performance through SSAS integration. Increased data processing efficiency by 45% resulting in faster report generation and analysis.• Automated data loading using SSIS and SSAS procedures, ensuring timely updates aligned with preset schedules for seamless operations. Reduced data loading time by 3 hours/days, improving data availability for decision-making. • Leveraged DAX to craft impactful visualizations in Power BI, delivering actionable insights that meet exacting customer specifications. Improved visualization effectiveness, leading to 20% increase in user engagement or decision-making speed.• Resolved complex data issues promptly, enhancing reporting accuracy and efficiency to meet stringent client demands. Achieved 90% reduction in data error rates, resulting in improved data reliability. • Engineered a solution enabling seamless export of over 150,000 rows, exceeding client expectations and bolstering satisfaction. Achieved 100% increase in customer satisfaction scores based on feedback surveys or ratings.• Implemented Selenium for automated data extraction from internal systems, enhancing report comprehensiveness and efficiency. Reduced data retrieval time by 30%, improving overall report turnaround time.

- Handling production defects, market defects: receive information from relevant departments, then analyzing to find out the root causes and appropriate solutions. + Identify improvement problem, improvement scope, improvement objective + Collect necessary data, identify potential causes + Apply QC 7 tools (Histogram, Fishbone, Pareto Chart, scatter Diagram, stratification, check list) to analyze and find the main causes based on the degree of influence of the cause on the problem needed handle +Find solutions to address the main causes, test the effectiveness of improvement activities by the methods of One-sample T-test, Pair Sample T-Test, ANOVA - Supplier quality improvement: based on quality history and production data, supporting analysis and improvement of critical defects according to the DMAIC method- Team leader General Management: Responsible for team operations, coordinating work on schedule, planning and conducting periodic supplier audits, and training members and suppliers in necessary knowledge and tools.