Welcome to my Data Analyst portfolio! This repository showcases my skills, projects, and experiences in the field of data analysis. Feel free to explore the various sections to get an insight into my capabilities.
- About Me
- Skills
- Projects
- Education
- Work Experience
- Contact Information
I'm Immaculate Obi, a passionate and resourceful data analyst with a thirst for insights and a drive to turn information into actionable knowledge. I possess a solid foundation in data analysis techniques, including data cleaning, wrangling, visualization, and basic modeling. I'm proficient in tools like Excel, SQL, Tableau, Google Looker Studio and PowerBi. My experience in previous projects has allowed me to hone my skills in analyzing complex datasets and presenting actionable insights. I'm a results-oriented individual with a strong work ethic and a collaborative spirit. I'm confident in my ability to quickly learn new skills and contribute meaningfully to any data-driven project.
- Data Cleaning and Manipulation.
- Critical thinking and Problem solving skill
- Data Visualization (using tools like Excel, Google Looker Studio, PowerBi, Tableau)
- Communication skill.
- SQL and Database Management
The project is a road accident dashboard created using Microsoft Excel. The dashboard shows statistics on road accidents for the years 2021 and 2022.
The goals of the project are to: Reduce the number of road accidents. Improve the safety of drivers. Provide insights into the causes of road accidents. Help policymakers make informed decisions about road safety.
The following tools and techniques were used to create the dashboard: Microsoft Excel: Excel was used to create the charts, graphs, and tables that are displayed on the dashboard. Data analysis: Data analysis techniques were used to clean and prepare the data for use in the dashboard. Data visualization: Data visualization techniques were used to create the charts, graphs, and tables that are displayed on the dashboard.
The project has had a positive impact on road safety. The dashboard has been used by policymakers to make informed decisions about road safety, such as investing in new safety measures and improving enforcement of traffic laws. The dashboard has also been used by drivers to learn about the risks of road accidents and how to stay safe.
The dashboard shows that the total number of casualties from road accidents in 2021 and 2022 was 41,7883. Of the total number of casualties, 1.7% were fatal, 14.2% were serious, and 84.1% were slight. The most common type of vehicle involved in road accidents was cars, which accounted for 79.8% of all casualties. The most common location for road accidents was Urban areas, which accounted for 61% of all casualties. The most common time of day for road accidents was during the day, which accounted for 79% of all casualties.
HR Analytics Dashboard
This Power BI dashboard appears to be focused on Human Resources (HR) analytics, providing insights into employee data. It features various charts and graphs to visualize key metrics related to employee demographics, attrition, job satisfaction, and age distribution.
Based on the metrics displayed, some potential goals could include:
Reducing employee turnover: By analyzing attrition rates across departments, age groups, and job roles, the HR department can identify areas with high turnover and implement targeted retention strategies. Improving employee engagement: Tracking job satisfaction ratings can help HR understand employee sentiment and identify areas where employees may be disengaged. Optimizing workforce demographics: Analyzing the age distribution of the workforce can help HR plan for future talent needs and ensure a balanced workforce.
The dashboard was clearly created using Power BI, a business intelligence tool from Microsoft. Data visualization: The dashboard utilizes various data visualization techniques, including bar charts, pie charts, and donut charts, to effectively present HR data. Data analysis: The creation of the dashboard likely involved data analysis techniques to clean, prepare, and transform the employee data for visualization.
Some potential benefits could include:Data-driven decision making: HR professionals can leverage the insights from the dashboard to make informed decisions about talent acquisition, retention, and workforce development. Improved employee experience: By understanding employee sentiment and identifying areas of concern, HR can implement initiatives to improve employee engagement and satisfaction.
Cost savings:Reducing employee turnover and improving engagement can lead to cost savings for the organization.
Project Title:
UEFA Champions League Dashboard
This Tableau dashboard is a visualization of the UEFA Champions League, a premier club football competition in Europe. It features a variety of charts and graphs to showcase historical data and statistics about the competition, including:
- Top 10 players by appearances
- Top 10 coaches by appearances
- Top goalscorers in a single season
- Most appearances in a single season
- Top clubs by played games
- All-time winners ranking
- Top 10 players by goals
- Top clubs by scored goals
The goals of this project are likely to: Provide a comprehensive overview of the UEFA Champions League's history and statistics. Highlight the most successful players, coaches, and clubs in the competition. Engage fans of the competition with interactive data visualizations. Potentially inform decision-making within clubs or the UEFA organization.
Tableau:The dashboard was clearly created using Tableau, a popular data visualization tool. Data acquisition: The creator likely gathered data from various sources, such as the official UEFA website, football databases, and historical records. Data cleaning and preparation: The data needed to be cleaned and prepared for visualization, which may have involved tasks like handling missing values, identifying outliers, and formatting data correctly. Data visualization: The dashboard uses various chart types, including bar charts, pie charts, and heatmaps, to effectively present the data.
The impact of this dashboard include:Increased fan engagement: The interactive visualizations and historical data can provide fans with a deeper understanding and appreciation of the competition. Informed decision-making: Clubs and the UEFA organization may use the data insights to make informed decisions about player recruitment, competition format, and marketing strategies. Educational resource: The dashboard can be used as an educational resource for students and researchers interested in sports data analysis.
Project Title:Coffee Shop Sales
This Excel dashboard appears to be designed to track and analyze sales data for a coffee shop. It includes various charts, graphs, and tables that provide insights into key metrics such as: Total revenue: The dashboard displays the total revenue generated by the coffee shop, potentially for a specific timeframe.
Transactions: The number of transactions made is shown, potentially broken down by day of the week or hour of the day.
Product types and categories: The dashboard categorizes and displays sales data for different types of coffee and other products sold, potentially including revenue and transaction counts for each.
Top products: The top 15 product types by transaction and revenue are highlighted.
Track and monitor sales performance: The dashboard provides a centralized view of key sales metrics, allowing the coffee shop owner or manager to track progress and identify areas for improvement. Gain insights into customer behavior: By analyzing transaction data by day, hour, and product type, the dashboard can reveal patterns in customer behavior and preferences. This information can be used to inform marketing and promotional strategies, product offerings, and staffing decisions. Improve profitability: By identifying best-selling products and peak sales times, the coffee shop can optimize its inventory and staffing to maximize profitability.
Microsoft Excel: The dashboard was clearly created using Excel, a spreadsheet software application. Pivot tables and charts: Pivot tables were likely used to summarize and organize the sales data, while charts and graphs were used to visualize the data effectively. Formulas and functions: Excel formulas and functions were likely used to calculate various metrics, such as total revenue, average transaction value, and product popularity.
The impact of this dashboard include:
Increased sales and revenue: By gaining insights into customer behavior and preferences, the coffee shop can make data-driven decisions to improve product offerings, promotions, and staffing, potentially leading to increased sales and revenue.
Reduced costs: The dashboard can help identify areas where the coffee shop can reduce costs, such as by optimizing inventory or scheduling staff during peak sales times.
Improved customer satisfaction: By understanding customer preferences and buying patterns, the coffee shop can tailor its offerings and service to better meet customer needs, potentially leading to improved customer satisfaction and loyalty.
This coffee shop sales Excel dashboard appears to be a valuable tool for coffee shop owners and managers to track sales performance, gain insights into customer behavior, and make data-driven decisions to improve profitability and customer satisfaction.
BSc in Economics, Tai Solarin University of Education, 2019 Relevant coursework: Google Data Analytics Certificate 2022
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