Mridula Sharma

Conducted analyses on datasets >10M using Python, SQL, Excel and Power BI, uncovering market trends that increased operational efficiency by 15%. Built reusable ETL scripts and automated dashboards enabling self-service analytics and improving data migration efficiency by 20%.

Analyzed legacy university data and designed transformations for BANNER migration, improving data accuracy by 30% and identifying 150+ discrepancies to increase reporting reliability. Collaborated with cross-functional teams to implement solutions ensuring 100% compliance and early system transition.

Developed automated Python ETL scripts and optimized SQL queries to reduce data retrieval time by 40% and consolidated multiple datasets into dashboards that improved operational accuracy and delivered a 15% efficiency gain. Provided data-driven strategic analysis that supported a 20% growth initiative in targeted segments.

Performed landscape analysis and insights generation for Microsoft IPG, reducing report generation time by 40% and coordinating a five-member team to accelerate time-to-productivity by 40%. Developed dynamic Excel dashboards to streamline client data analysis and improve decision-making efficiency.

Collected and prepared large volumes of patent data from multiple offices, improving data processing efficiency by 10% and applying database modeling techniques that increased data accuracy by 15%. Produced market analysis reports on UI technologies (AR, gesture recognition, smart TV) that informed strategic decisions.

Developed and optimized client-side logic using JavaScript and jQuery, improving application speed by 20% and scalability by 15%.

Pursuing a Master of Science in Computing (Data Analytics) at Dublin City University since September 2021, focusing on applied data analytics techniques.

Began a Bachelor of Technology in Computer Science and Engineering at Amity University in May 2012.