Sakiru Akinpelu

• Performing data cleaning, EDA, and root cause analysis on e-commerce and entertainment datasets,
identifying and resolving missing values, duplicates, and structural inconsistencies.
• Completed advanced SQL module — authored 35+ queries across PostgreSQL (Chinook) and MySQL datasets,
covering joins, subqueries, aggregation, and window functions.
• Built a COVID-19 Power BI dashboard using Johns Hopkins CSSE data with DAX measures, bookmark-based
year filter buttons, and geographic drill-down views for executive-level reporting.
• Generating business insights through statistical analysis and visualizations using Python (Pandas, Matplotlib,
Seaborn); all work documented in structured Jupyter Notebooks.

• Inherited a disorganized HR employee dataset with inconsistent fields and missing values; standardized it
end-to-end by deriving computed columns (Employment Status, Employee Tenure) and resolving cross
department naming inconsistencies.
• Engineered 10+ pivot table models with advanced Excel logic (IF, COUNTIF, nested lookups) to analyze salary
band distribution, attrition risk, and workforce tenure patterns across departments.
• Designed and delivered an interactive HR Analytics Dashboard with KPI cards, dynamic slicers, and drill
through visualizations — enabling management to self-serve workforce insights without analyst intervention.

• Conducted multi-tool analysis (SQL, Python, Tableau) across diverse datasets, generating insights that
translated into a 25% increase in actionable business recommendations adopted by product and leadership
teams.
• Built a suite of interactive Tableau dashboards that reduced average decision-making latency by 30% by
surfacing KPIs previously buried in static weekly reports.
• Implemented rigorous data cleaning and validation pipelines (deduplication, outlier detection, schema
enforcement), reducing data errors by 30% and cutting erroneous data entry by 25%.
• Delivered stakeholder-facing visualizations that communicated complex statistical findings to non-technical
audiences, resulting in a 40% increase in data-informed decisions across teams.

• Built and maintained a student performance tracking system with real-time dashboards, contributing to a
10% improvement in overall student grades.
• Designed and analyzed A/B tests on new educational tools across 1, 000+ learners; findings drove a 15%
increase in engagement and a 10% lift in course completion rates.
• Automated data ingestion from 3+ online learning platforms using Python scripts, eliminating manual data
entry errors by 80% and reclaiming 20 hours/week for the analytics team.
• Unified data pipelines from 5+ fragmented source systems, reducing cross-source inconsistencies by 90% and
establishing a single source of truth for institutional reporting.

• Led design of a data-driven program evaluation framework across 50+ workshops, surfacing performance
patterns that improved program effectiveness by 25%.
• Analyzed participant feedback and performance data from 1, 000+ workshop attendees, delivering insights
that raised satisfaction scores by 18%.
• Built a survey analysis and reporting system for grant applications, securing a 30% increase in grant funding
through stronger data-backed submissions.
• Automated ETL processes across internal systems, reducing data processing time by 60% and freeing analysts
for higher-value work.