Collins Okakwu

<p>Perform in-depth analysis of procurement, supplier, cost and operational data using Advanced Excel, SQL, Power BI and Python to support commercial and operational decision-making.</p><p> Use Advanced Excel functions, formulas and structured checks to analyse data, compare sources and identify trends, anomalies and exceptions.</p><p> Clean, review and validate data from multiple business systems, identifying missing, inconsistent or duplicate information and coordinating corrective action with stakeholders.</p><p> Reconcile financial and operational records to ensure reporting is accurate, complete and consistent before it is used in management decisions.</p><p> Develop recurring Excel and Power BI reporting outputs that communicate supplier costs, compliance, operational KPIs and performance trends clearly.</p><p> Translate stakeholder questions into practical analysis, selecting the most appropriate data, measures and presentation format for the business need.</p><p> Document calculation logic, assumptions, validation steps and reporting methodologies to ensure repeatability, transparency and auditability.</p><p> Identify underlying drivers behind unusual movements using variance, trend and root-cause analysis, then present concise recommendations to senior stakeholders.</p><p> Automate and streamline recurring reporting processes using Excel, Power Query and Power BI, reducing manual effort while improving consistency.</p><p> Work independently across multiple analytical priorities in a fast-paced environment while maintaining high standards of accuracy and attention to detail.</p>

<p>Prepared and validated data for SQL and QlikView reporting, supporting accurate operational and management information.<br>
Tested dashboard outputs, reconciled figures and investigated inconsistencies before reports were released to users.<br>
Translated stakeholder reporting requirements into KPI views, tables and visualisations.<br>
Maintained clear reporting documentation, definitions and data-quality standards.</p>

<p>Analysed large workforce datasets using statistical and Excel-based techniques to identify trends, patterns and planning implications.<br>
Prepared executive reports, tables, charts and forecasts that translated complex information into clear business insight.<br>
Validated datasets, investigated data inconsistencies and implemented corrective measures before reporting.<br>
Documented analytical methods and presented evidence-based recommendations to senior stakeholders.</p>

<p>Used Excel to analyse supplier, inventory, cost and operational information and produce KPI reports for planning and project decisions.<br>
Reviewed and validated reporting data, investigated discrepancies and contributed to consistent data standards.<br>
Prepared project reports, documentation and analytical summaries for cross-functional stakeholders.</p>

<p>Led end-to-end business data analysis using Advanced Excel, SQL, Power Query and Power BI across commercial, procurement and operational functions.</p><p> Prepared, cleaned and transformed large datasets from multiple sources, applying validation checks and reconciliation techniques before analysis.</p><p> Used Excel-based analytical methods including formulas, variance analysis and structured comparison to answer ad hoc and recurring business questions.</p><p> Created concise reports, tables, charts and dashboard outputs that helped senior stakeholders understand performance and take evidence-based action.</p><p> Identified trends, anomalies, risks and improvement opportunities across complex datasets using root-cause, statistical and performance analysis.</p><p> Developed KPI definitions, reporting standards and documentation covering calculations, assumptions and interpretation of analytical outputs.</p><p> Automated recurring reporting using Excel, SQL, Power Query and Power BI, improving reporting speed, repeatability and data integrity.</p><p> Worked directly with project stakeholders to clarify data requirements and ensure analysis addressed the underlying business question.</p><p> Presented analytical outcomes clearly to technical and non-technical audiences through dashboards, presentations and written commentary.</p><p> Mentored colleagues on Excel, Power BI, reporting standards and data-quality best practice.</p>

<p>Reviewed, cleaned and analysed operational and clinical datasets using Excel, SQL, Python and Power BI to support service decision-making.</p><p> Used structured validation checks to identify data inconsistencies, missing information and reporting errors and worked with users to resolve them.</p><p> Produced recurring management reports and dashboards that communicated service trends, performance issues and improvement opportunities.</p><p> Translated operational questions into analytical requirements and documented the methods and logic used to produce reports.</p><p> Analysed structured and unstructured information to identify recurring patterns, anomalies and potential root causes.</p><p> Presented complex findings in clear, accessible language to non-technical users and operational managers.</p><p> Maintained reporting documentation, quality standards and repeatable analytical processes in a data-sensitive environment.</p>

<p>Analysed customer, sales and commercial datasets using Excel, SQL and Power BI to identify trends, revenue opportunities and performance issues.</p><p> Cleaned and validated source data, identified inconsistencies and prepared reliable datasets for recurring and ad hoc analysis.</p><p> Created charts, dashboards and KPI reports that enabled commercial stakeholders to understand customer engagement and sales performance.</p><p> Used Excel and SQL to investigate business questions, compare performance and explain notable variances.</p><p> Automated recurring reporting and improved the accuracy and consistency of management information.</p><p> Presented analytical conclusions and recommendations clearly to stakeholders with different levels of technical knowledge.</p>