Vibhor Agarwal

• Spearheaded data cleansing initiatives for global UNIFY project, migrating 100K+ master data records from SAP ECC to SAP S/4HANA with 99.5 % accuracy, eliminating critical discrepancies across multiple business domains. • Engineered automated KPI dashboards using Excel VBA and Python, reducing monthly reporting time by 60% and enabling real-time data quality tracking for C-level stakeholders. • Optimized data extraction workflows by developing custom SAP queries to merge multiple tables, cutting manual export time by 75% and improving data analyst team productivity. • Applied UDM (Unified Data Management) standards to scope and validate 50+ master data fields, ensuring compliance with global data governance policies across ERP systems. • Leveraged advanced SQL and Python for large-scale data validation of 1M+ records, identifying and resolving data anomalies that manual analysis could not detect. • Integrated cross-platform data from BFO, SAP, and PIM systems to build comprehensive KPI frameworks measuring data quality and migration progress.

• Analyzed 50K+ customer policy records to identify renewal patterns, uncovering 23% increase in post-expiry renewals for specific demographics. • Evaluated customer engagement metrics for newly launched products, providing data-driven recommendations that influenced marketing strategy adjustments. • Designed and built interactive dashboards visualizing key performance metrics, enabling leadership to track customer behavior trends and product adoption rates. • Delivered actionable insights through advanced Excel analytics including pivot tables, VLOOKUP, and conditional formatting to enhance customer retention strategies.

• Built comprehensive sales analytics framework tracking daily revenue, customer traffic patterns, and peak operating hours to optimize inventory management and reduce waste by 18%. • Conducted product lifecycle analysis across seasonal variations, implementing data-driven procurement strategies that improved profit margins by 12%. • Monitored microeconomic indicators and customer feedback data to refine product offerings and pricing strategies, increasing customer satisfaction scores.

• Maintained 97-100% quality benchmarks for AI/ML training datasets through rigorous auditing protocols, ensuring high-accuracy model inputs. • Analyzed content performance metrics using Excel and Python, delivering insights that enhanced QA processes and operational efficiency by 15%. • Contributed to quality assurance framework development through detailed QASA reporting, optimizing data validation workflows and reducing error rates.

SAP - MM(Module)

SAP

Generative AI Mastermind

Outskill

Google Data Analytics

Coursera

Microsoft Excel - Excel Begineer to advance

Udemy

Ask questions to make Data-driven decision

Coursera

Python for Everybody

Coursera