ABIGAIL JOHNSON

Insight-driven analytics professional with experience turning high-volume logistics and business datasets into dashboards and operational improvements. Skilled in SQL, Excel, Power BI, Tableau, and Python (Pandas, NumPy) with a strong focus on data accuracy, anomaly detection, and KPI reporting. Background in business intelligence, data operations, and platform analytics supports roles across analysis, reporting, and data-supported decision functions.

Customer Transaction Analysis

• Identified purchasing trends across 1,000+ customer transactions by analyzing data with Python and Pandas, improving simulated campaign targeting efficiency by 15%.
• Reduced dataset inconsistencies by 30% by implementing automated data cleaning and validation workflows using structured Pandas logic.
• Generated an analytical report defining 5 key customer segments, enabling data-informed strategy recommendations for business decision modeling.

Database Management System

• Designed a 15-table MySQL database by applying normalization and indexing, reducing query processing time by 40% in structured test scenarios.
• Improved data retrieval efficiency by 25% by writing optimized SQL joins and aggregation queries for multi-table analytics.
• Strengthened database integrity by enforcing constraints and schema validation, preventing invalid entries and improving query reliability.

BI Dashboard Delivery Simulation

• Developed Power BI and Tableau KPI dashboards by integrating structured logistics datasets, improving reporting clarity and reducing manual compilation time by 35% in simulated leadership workflows.
• Automated metric calculations using DAX, decreasing formula build time by 20% while improving visualization accuracy.
• Designed anomaly tracking visuals that improved insight delivery speed for operations review by 30%.