My work

Portfolio

Introduction to the Analysis of Non-Economic Determinants of Happiness with Tableau and R.

This research emerges from personal observations made across diverse countries, where an unexpected contrast was noted: individuals in economically less affluent countries often appeared more outwardly happy than those in wealthier, “first-world” nations. This observation sparked curiosity and scrutiny of the World Happiness Report, where paradoxically, some of the highest-ranked nations in terms of happiness also exhibited high suicide rates. This phenomenon highlighted the complex and multidimensional nature of happiness and well-being, extending beyond purely economic metrics like GDP.

Grounded in psychology, this study adopts a subjective well-being approach to assess happiness, focusing on intrinsic and environmental factors such as mental health and sunlight exposure. Psychological research, particularly the work of Ed Diener and the positive psychology movement, emphasises that subjective well being measured by individual perceptions of life satisfaction, emotions, and mental health provides a more nuanced and accurate understanding of happiness compared to external metrics like income. To align with this perspective, traditional economic indicators, especially GDP, are removed from the analysis, allowing an examination of happiness influenced by non-economic variables.

This modified approach integrates factors like sunlight exposure, suicide rates, and depression prevalence. Each variable was chosen for its potential psychological and environmental impact on well-being. Sunlight, for example, has complex links to mental health, often varying by geography and seasonality. Likewise, high suicide rates and depression can signify mental health challenges within a population, which directly impact happiness levels, even in economically prosperous regions.

Through this model, the analysis aims to broaden the understanding of happiness by examining predictors beyond wealth. This perspective encourages policymakers to consider mental health, environmental quality, and social well-being in the pursuit of national happiness, offering new pathways for enhancing well-being, especially in nations with limited economic resources. In essence, this research advocates for a holistic approach to measuring happiness, recognizing that true well-being is deeply rooted in social, mental, and environmental factors rather than solely in economic prosperity.

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Data Analytics Projects

A showcase of diverse data projects highlighting skills in data cleaning, analysis, visualisation, and application development using SQL, R, ggplot2, Shiny, and more.

Data Cleaning with R: A Journey in Efficient Data Preparation.

R Cleaning

Click here to explore my portfolio project, showcasing data cleaning techniques in R, inspired by the guidance of Dr. Greg Martin.

DPLYR

Discover meaningful patterns and trends.

Unlock the power of data analysis with R, DPLYR, and GGPLOT2. .Discover meaningful patterns and trends.

TIDYVERSE

Data wrangling with tidyverse

Utilize R to filter, subset data, identify missing values, select specific columns, delay the appearance of a column, reorder rows, arrange by specific criteria, and apply mutations.

SHINY APP

Sales Performance Dashboard

This Shiny app provides a real-time overview of key sales metrics for a hypothetical company, helping to monitor sales volume, revenue, customer acquisition, and profits across regions and product categories. It visualizes trends through interactive charts, offering insights into segment performance, profit margins, and regional sales distributions, empowering data-driven decisions to optimize sales strategies and customer engagement.

MySQL

Analyse Dataset in a Model Car Database with MySQL Workbench

GGPLOT2

I analysed global development trends

using the Gapminder dataset and visualized the results with ggplot2. Key metrics such as GDP per capita, life expectancy, and population growth were explored across different countries and continents over time. The visualizations revealed patterns of economic growth, health improvements, and demographic shifts, highlighting disparities between regions. These insights were represented through scatter plots, line charts, and facet grids for better comparison.

Empower Data-Driven Decisions

Digital Marketing Campaign Dashboard Analysis

Description

This Tableau dashboard presents an in-depth analysis of a digital marketing campaign’s performance. Key metrics such as sales distribution, ROI by category, segment performance, and previous month’s sales are visualized for actionable insights.

What Problem Does This Analysis Solve?

  • Problem: Lack of clarity on the return on investment (ROI) and regional sales performance, leading to inefficient allocation of marketing resources.
  • Solution: By leveraging Tableau’s data visualization capabilities, this dashboard identifies high-performing categories, evaluates geographic sales distribution, and highlights the most effective marketing channels.

Key Highlights:

  • ROI Breakdown: Displays ROI for Firepits, Grills, and Patio Furniture, enabling targeted budget adjustments.
  • Geographic Analysis: Maps sales data by state, offering insights into regional performance.
  • Quarterly Trends: Visualizes sales trends over time for better forecasting and resource planning.
  • Top Segment Analysis: Highlights the most effective segment (e.g., “Website”), facilitating optimization efforts.
  • Word Cloud: Uses a word map to visually represent campaign keyword focus.

By solving these challenges, the dashboard empowers decision-makers to optimize marketing strategies for higher efficiency and better outcome

Exploratory Dashboard for Profit Analysis

Description

This Tableau dashboard serves as an exploratory tool to analyze profit trends, identify high-performing product categories, and assess regional profitability.

Key Use and Benefits:

  • Interactive Profit Analysis:
  • Product Breakdown: Bar chart highlights profit contribution by sub-categories within Furniture and Office Supplies.
  • Geographic Insights: Profit by state map enables regional comparison for targeted improvements.
  • Temporal Analysis:
    • Profit Over Time: Line chart reveals trends in profitability, aiding in historical performance reviews.
  • Relationship Discovery:
    • Sales vs. Profit Scatter Plot: Uncovers correlations between sales and profit across regions for strategic planning.

Stakeholder Application:

  • Decision-Makers: Identify areas of profit growth and potential loss for actionable strategy adjustments.
  • Sales Teams: Pinpoint regions and categories for sales optimization.
  • Analysts: Explore detailed trends to support data-driven recommendations.

This dashboard fosters deeper insights into business performance, empowering stakeholders to make informed decisions