By analyzing patterns in customer visits, spending, and menu item popularity, potential areas for marketing initiatives were identified. Before implementing any promotions, predictive analysis was used to assist in data-driven decision-making regarding net gain or loss for the business.
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In this case study, I assisted a local business owner, 'Danny', in optimizing his Pizza Runner business through data analysis. Utilizing my skills in SQL and PostgreSQL, I cleaned and organized data from the pizza_runner database schema. Through data analysis, I identified key areas for improvement such as pizza metrics, runner and customer experience, ingredient optimization, pricing, and ratings. My findings were used to make data-driven decisions, resulting in increased efficiency and profitability for the business.
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The analysis examined various factors to determine trends in bike purchases, with the aim of implementing data-driven marketing strategies. Factors such as average income, customer commute, number of children, and customer age were evaluated to identify patterns or correlations between these factors and bike purchases. The goal of the analysis was to improve marketing decisions and increase the chances of successful bike sales promotion.
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In this project, a historical analysis was conducted to explore patterns in the top 400 best-selling video games created between 1977 and 2020. A dataset on game sales, including critics and user reviews, was analyzed using SQL to determine whether or not video games have improved as the gaming market has grown over time. The goal of this project was to identify trends and insights that could potentially inform future game development and marketing strategies.
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In this project, a dataset containing 12.6k rows of baby names from the last 101 years was analyzed. The dataset included 3 additional variables such as the year of birth and gender. The goal was to identify trends in popularity and offer data-driven insights for different name selection scenarios. The analysis was performed using advanced window functions and common table expression queries in Postgresql.
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This explorative study used data from Our World in Data to analyze data on the global spread of COVID-19, including infection and death rates, as well as vaccination rates. The goal was to identify patterns and trends in the data in order to better understand the spread of the virus and inform decision-making around public health interventions and policy. The analysis used advanced data statistical analysis tools to identify key insights and trends in the data.
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This was a data analysis project that used the Stack Overflow Data Explorer to examine the relative popularity of programming languages over time. The goal of the analysis was to identify trends in language usage and determine which languages were growing in popularity and which were declining. The results of the analysis showed that R, Python, Java, and JavaScript were growing in popularity, while other languages like C# and C++ were shrinking. The analysis was done to understand the trend of programming languages' popularity over time, in order to make informed decisions about which languages to invest more money and time in learning or teaching.
View ProjectThis list of finished data visualizations includes PowerBI visualizations in static version only. I apologize for any inconvenience.
A dashboard that displays key metrics such as revenue, profit growth, top performing countries and customers, and product popularity to aid the CEO and CMO in expanding the company, using cutting-edge visualization techniques and a user-friendly format for easy identification of areas for improvement and expansion opportunities.
View VizA dashboard that displays various visual metrics of demographic data for each region in South Korea, including suicide, birth, death, marriage, and divorce rates. It allows for easy comparison and understanding of population dynamics and cultural trends.
View VizThis data visualization showcases the top 10 states in the United States with the highest population change (gain) and the top 10 states with the lowest population change (loss) from 2021 to 2022. By analyzing data on state population migration, it is clear that certain states have experienced a significant increase in population, while others have seen a decline. The visualization provides valuable insights into population trends and can be used to inform decisions related to resource allocation and planning.
View VizA data analysis of a Superstore's profits, sales, and popular products. The analysis included a breakdown of profits by year, total sales orders by quarter, the top ten most popular products, the top ten highest earning products, and sales by state. The analysis aimed to provide insights into the performance of the business and identify areas for potential improvement.
View VizThe AirBNB analysis visualization shows profitable areas, average rental cost by bedroom type, and optimal rental listing time. It also compares availability of different bedrooms in different areas to inform property investment decisions, giving a comprehensive overview of the rental market and supporting strategic decisions.
View VizThe visual dashboard displays the top causes of death in 2010 and 2019, with rates and % change, and also death rates by marital status with % change over the same time period. The dashboard provides a clear and concise overview of the data, making it easy to identify trends and patterns in mortality rates. This information can be used to inform public health policies and interventions to target specific causes of death and populations at risk.
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