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Data Analyst with less than a year in SQL, Excel, and Power BI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst with hands-on experience in SQL, Excel, Power BI, and Python, specializing in data cleansing, preparation, and visualization. Proficient in developing dynamic dashboards and interactive reports to provide actionable insights into business performance and trends. Eager to leverage analytical skills to drive data-driven decision-making.
University of Professional Studies Accra (UPSA)
BACHELOR OF BUSINESS ADMINISTRATION · Supply Chain Management, Total Quality Management, Risk Management, Managerial Accounting, Global Business, Operations Management, International HR Management
N/A – June 30, 2022
GHANA REVENUE AUTHORITY(GRA)
National Service
November 1, 2022 – September 1, 2023
India
DATA PROFESSIONAL SURVEY
October 1, 2024 – October 1, 2024
Designed and developed an interactive Power BI dashboard to visualize key trends, including demographics, career paths, and skills of data professionals. Cleaned and transformed raw survey data by utilizing Power Query for effective data preparation and integration. Leveraged DAX (Data Analysis Expressions) to create calculated measures and columns for advanced analytical insights. Built dynamic visualizations, including bar charts, line charts, maps, and KPIs, to present findings in a visually compelling and user-friendly format.
NASHVILLE HOUSING
August 1, 2024 – August 1, 2024
Populated missing property addresses using the ISNULL function combined with self-joins and UPDATE statements to ensure data completeness and accuracy. Standardized date formats by using the CONVERT function to transform raw date values into a consistent format and updating the SaleDateConverted column for uniform analysis. Decomposed complex address strings into individual components (Address, City, State) by leveraging SUBSTRING and CHARINDEX functions, enabling more granular geographic analysis. Standardized categorical data in the SoldAsVacant field by using a CASE statement to replace binary values ('Y', 'N') with descriptive labels ('Yes', 'No') for better interpretability. Split owner address fields into structured components (OwnerSplitAddress, OwnerSplitCity, OwnerSplitState) using the PARSENAME and REPLACE functions, improving data organization and usability. Eliminated duplicate records by employing the ROW NUMBER function within a Common Table Expression (CTE) to identify and remove redundant entries. Optimized database structure by dropping unused columns, reducing storage overhead, and improving query performance.
CORONAVIRUS (COVID-19)
July 1, 2024 – July 1, 2024
Leveraged subqueries and GROUP BY to aggregate data and identify key patterns, such as the highest infection rates and vaccination impacts. Performed joins between datasets (Covid Deaths and Covid Vaccinations) to combine related data for analysis of correlations between vaccination rates and infection trends. Used GROUP BY to aggregate results at a country or regional level, aligned with metrics like maximum infection rates or percentages. Used WITH clauses for CTEs to break complex queries into manageable steps, improving readability and reusability of queries. Defined views to encapsulate reusable queries for exploring trends like total cases, deaths, or vaccinations over time. Used window functions with PARTITION BY to rank countries or compute running totals and percentages within specific groups (e.g., by continent or region). Utilized ORDER BY to sort results by multiple columns, ensuring data was presented in a logical and readable manner. Leveraged aggregate functions such as MAX to find the highest infection counts or percentages and SUM to compute cumulative values like total cases or deaths.
COFFEE SALES DASHBOARD
April 1, 2024 – April 1, 2024
Utilized advanced Excel functions, including XLOOKUP, INDEX MATCH, and multiple IF statements, to efficiently process and analyze large datasets. Conducted data cleansing and preparation, such as identifying duplicates, converting ranges to tables, and ensuring consistent formatting for analysis readiness. Designed and developed dynamic Pivot Tables and Pivot Charts to uncover key metrics and visualize trends in coffee order patterns. Built a visually compelling and user-friendly dashboard that provided actionable insights into customer order trends and business performance.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in data analysis, covering various domains like sales, professional surveys, and public health (COVID-19). This diversity suggests adaptability and a willingness to explore different data challenges. The educational background in Business Administration with a focus on Supply Chain Management, combined with a Data Analytics Cohort, indicates a structured approach to learning and a desire to align business understanding with technical skills. The national service experience at a government agency shows exposure to a formal work environment. However, the projects are all personal, and there is limited information on collaborative team environments or contributions to open-source projects, which could provide more insight into cultural fit within a dynamic team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work with complex datasets and present findings clearly, which suggests good analytical and problem-solving skills. The experience at Ghana Revenue Authority shows collaboration with audit teams and supporting decision-making, indicating a capacity for teamwork and contributing to operational processes. However, the resume does not provide explicit details on communication style, stress handling, or direct team collaboration in a data-focused project context beyond supporting roles.