•Reviewed data provided by the dealer acquisition team for accuracy and completeness, ensuring compliance with company standards.•Analyzed and presented data using excel and power bi on onboarded dealers to relevant colleagues and teams, facilitating informed decision-making.•Prepared reports on dealer and account managers performances as necessary, highlighting key metrics and trends.•Maintained business standard operating procedures (SOPs) for data integrity and dealer acquisition processes.•Identified and escalated data inaccuracies and gaps within expected timelines, ensuring timely data correction.•Ensured that data being fed into the database on dealers is true and accurate which reduce data errors by 95%•Utilized data analysis skills to identify customer and dealer behavior which helped in management decision

•Leveraged data analysis tools (Excel, Power BI, Tableau) to generate insights that informed sales management decisions, leading to improve customer retention rate by 80%.•Performed data cleaning and analysis on the active contract report to ensure client authenticity using Excel. This process identified and rectified discrepancies, improving data accuracy for [for the finance team.•Developed and analyzed customer behavior dashboards using data visualization tools. These dashboards revealed key trends such as customer churn enabling the sales team] to develop targeted marketing campaigns or optimize product offerings.•Planned and designed reports, establishing procedures for efficient data presentation and clear communication of insights to stakeholder

-I improved Excel dashboard utilisation by 50% to better understand employee turnover.-Worked with teams to generate insights on gas prices and identified patterns and trends on prices across the world.-Prepared reports that effectively communicated trends, patterns and predictions in relation to the business objectives.- Collected structured and unstructured data from several sources especially open data (kaggle, data.gov)-Created a start-up called the Vortex that aims to reduce banking fraud by 100% with the use (building) a machine learning model-Processed, cleaned and verified data which helped draw accurate findings and insights.-Sourced missing and organized data with SQL to be able to identify each employee, their position and the salary it comes with.

-Summarized news prior to the 2020 elections from newspapers and TV using SPSS daily which helped us give insights and make data driven decisions for our client.- Used the information gathered from SPSS to write reports for our client which caused them to win extra 10,000 votes in the Ashanti Region