SQL/Tableau Projects

Welcome to my collection of SQL-Tableau projects, showcasing my skills in data analysis, database management, and data visualization. These projects, developed for school, work, or personal exploration, cover a range of topics like deriving actionable insights from an online shopping dataset, employing SQL for data exploration and Tableau for creating interactive visualizations.

Feel free to navigate through the projects listed below, each providing a unique perspective on data-driven decision-making.

Project Index

1. City of Angel's Watch: Mapping LA's Crime Dashboard
2. Coronavirus (COVID-19) Dashboard
3. U.S. Police Shootings Dashboard
4. Online Shopping Analytics Project

Projects

City of Angel's Watch: Mapping LA's Crime Dashboard with Tableau and Python (April 2024)

• Folders: City of Angel's Watch: Mapping LA's Crime
• Objective:
  • Illuminate the complex dynamics of crime in Los Angeles through an analytical and narrative approach, fostering data-driven decision-making and community engagement.
• Key Points:
  • Engineered a narrative/analytical Tableau dashboard featuring interactive visualizations such as heatmaps, KPIs, and bar charts to provide an in-depth analysis of crime trends, hotspots, and demographic patterns in Los Angeles.
  • Leveraged Python to clean and prepare data, utilizing libraries like Pandas, NumPy, and Matplotlib to transform raw crime data into structured, actionable insights while handling missing values and standardizing data formats.
  • Conducted a comprehensive data-driven storytelling approach that combined visualizations with narrative elements to highlight key insights and patterns, supporting informed decision-making for policymakers and community leaders.
• Technical Highlights:
  • Implemented advanced Tableau features, including parameter controls and dashboard actions, enabling dynamic filtering and drill-down capabilities for personalized crime data analysis.
  • Merged and normalized multiple datasets from the LA Open Data portal, ensuring structural consistency and resolving temporal data discrepancies.

Coronavirus (COVID-19) Dashboard with SSMS and Tableau (February 2024)

• Folders: COVID-19 Dashboard
• Objectives:
  • Uncover actionable insights and trends within COVID-19 data to facilitate informed decision-making and deepen understanding of the pandemic's impact on a global scale.
• Key Points:
  • Engineered an intuitive and comprehensive Tableau dashboard, serving as a visual compass elucidating critical metrics and fostering a holistic understanding of the pandemic's impact.
  • Leveraged advanced SQL queries to meticulously extract, cleanse, and transform COVID-19 data to lay a solid groundwork for subsequent analysis and visualization.
  • Conducted in-depth exploratory data analysis (EDA) on a large-scale COVID-19 dataset containing over 370,000+ rows and 31 columns, uncovering nuanced trends and patterns.
• Technical Details:
  • Utilized SQL window functions to calculate rolling cumulative sums and percentage changes, enabling nuanced trend analysis and comparison over time using JOINs and Common Table Expressions (CTEs).
  • Tools/Formats: Excel for dataset management, SQL Server Management Studio for database administration and querying, SQL for data exploration and analysis, and Tableau for dashboard design and visualization.

U.S. Police Shootings Analysis Dashboard with Tableau (February 2024)

• Folders: U.S. Police Shootings Analysis Dashboard
• Objectives:
  • Unveil insights into U.S. police shootings from 2015 to September 2022 through interactive Tableau visualizations, highlighting key demographic trends, circumstances, and geographical patterns.
• Key Points:
  • Utilized Tableau to develop interactive visualizations showcasing demographic breakdowns, armed encounters, and geographic hotspots.
  • Employed advanced filtering techniques to enable users to explore specific aspects of police shootings, such as gender, signs of mental illness, and race.
  • Integrated tooltips to provide users with additional context and insights upon hovering over visual elements.
• Technical Details:
  • Leveraged Tableau's capabilities to create diverse visualizations, including heatmaps, stacked bar graphs, highlight tables, and pie charts.
  • Implemented advanced filtering functionalities to enhance user interactivity and tailor the analysis to individual preferences.

Online Shopping Analytics with SQL Server Management Studio and Tableau (December 2023)

• Folders: Online Shopping Analytics
• Objectives:
  • Explore and analyze an online shopping dataset to derive valuable insights into customer behavior, product sales, and transactional patterns. The project showcases the integration of SQL for database management and Tableau for creating compelling visualizations.
• Key Points:
  • Utilized SSMS to develop a robust database structure with three tables: Customer, Product, and Transactions based on an imported dataset from Kaggle.
  • Executed SQL queries to employ advanced analytics and populate the newly created database.
  • Developed a diverse set of interactive dashboards that utilized bar graphs, area charts, dual-axis graphs, packed bubble charts, and tree maps to provide insights.
• Technical Details:
  • Integrated SQL findings into visual representations for enhanced data-driven insights.
  • Tools/Formats: Dataset in .xlsx, SQL Server Management Studio for database management, SQL for database creation, Tableau for visualizations.
  • Dataset: https://www.kaggle.com/datasets/jacksondivakarr/online-shopping-dataset/data