• Performed analysis on NYC Food Inspection dataset that contains food inspections carried out in the five boroughs of New York from 2017 till March 2022
• Designed dimensional models to create Fact and dimensional tables respective to New York city
• Utilized Alteryx to execute data profiling, transformations employing regular expressions and parsing techniques, and data-cleaning operations
• Created an extensive collection of 100+ reports and dashboards using Tableau and Power BI to highlight inspections, violations, and severity over time
Conduct in-depth data profiling with Alteryx to gain comprehensive insights into the food inspection data, ensuring data quality and accuracy for subsequent analysis.
Create a dynamic dimensional model using ER/Studio to facilitate efficient data analysis, enabling exploration of food inspection data across various dimensions and hierarchies.
Designed and treamlined data integration with Talend and Alteryx, merging data from multiple sources for robust and reliable profiling.
Develop interactive dashboards using Power BI and Tableau to visualize key insights, answering critical business questions such as inspection trends, pass vs. fail rates, and types of violations. Below are the some visuals in PowerBi AND Tableau:
Leveraging dimensional modeling, data profiling, and data visualization helped address key business questions:-
- Top ten most inspected and worst-performing establishments based on inspection outcomes over the last two full years
- Number of food inspections over time.
- inspection results (pass vs. fail), grades, scores, or score ranges, and the number, severity, and types of violations reported.
- Food establishments based on attributes such as business type, cuisine, and city boroughs.
Skills and tools: SQL, Alteryx, PowerBi, Python, ER/Studio, Tableau
Concepts: EDA, Data Cleansing, Data Manupulation, Dealing with outliers and missing values, Data Modeling, Data Integration, ETL, Dashboard Creation, Data visualization, Data Analysis