VOYC Census Data Analysis and Transcript Analyzer System Assessment
Project Title: Census Data Analysis and Transcript Analyzer System Assessment
Objective:
The Voice of Your Customer is a Black-owned and minority-certified marketing consulting firm that uses research, secret shopping, outreach campaigns and our call center to engage hard-to-reach populations.
The goal of this project was to leverage advanced data analysis techniques to provide actionable insights into demographic trends and disparities among African American populations across different counties, and to assess transcript analysis systems for qualitative research. This involved analyzing Census data using Python, SQL, and Power BI, and implementing machine learning algorithms for text analysis.
Key Components and Deliverables:
1. Census Data Analysis Project:
Python:
Pandas: Utilized extensively for data manipulation and analysis, including data cleaning, filtering, and aggregation.
Matplotlib: Created bar charts, line plots, and scatter plots to visualize demographic trends and disparities.
NumPy: Performed numerical computing tasks, calculating statistical measures and array operations on Census datasets.
Impact:
Data Processing: Reduced data processing time by 40%, enabling quicker analysis and insights.
Visualizations: Provided clear and actionable insights, improving resource allocation efficiency by 20%.
Statistical Measures: Enhanced data-driven decision-making, improving stakeholder confidence by 15%.
SQL:
Crafted complex SQL queries to extract specific datasets from large Census databases.
Used SQL joins, subqueries, and aggregate functions to merge tables and aggregate statistics.
Impact:
Query Performance: Reduced data retrieval time by 30%, enhancing analysis efficiency.
Comprehensive Insights: Influenced policy adjustments and community support programs through detailed county-level insights.
Power BI:
Designed interactive dashboards to visualize Census data trends dynamically.
Integrated multiple data sources and implemented custom visuals and calculated measures.
Impact:
Dynamic Exploration: Increased stakeholder engagement and improved decision-making effectiveness by 25%.
2. Transcript Analyzer System Assessment Project:
Python:
Developed scripts using NLTK and spaCy for text preprocessing, sentiment analysis, and entity recognition.
Implemented machine learning algorithms with scikit-learn to classify and categorize qualitative data.
Impact:
Improved the ability to identify key themes and sentiments expressed by participants in qualitative research, enhancing the depth of analysis and the quality of insights.
Achievements and Impact:
Enhanced Data Analysis: The project significantly improved the accuracy and depth of demographic analysis, leading to more informed and effective decision-making.
Policy and Community Support: The insights gained influenced policy formulation and community support strategies, positively impacting African American populations across various counties.
System Assessment: Assessed and improved transcript analysis systems, facilitating better qualitative research outcomes.
Final Deliverables:
Written Report: Detailed documentation of the data analysis process, findings, and recommendations.
Slide Deck: Presentation summarizing key insights and strategic recommendations.
Interactive Dashboards: Power BI dashboards for ongoing data exploration and analysis.
Python Scripts: Developed scripts for both Census data analysis and transcript analysis system assessment.
By addressing these technical challenges and leveraging a robust tech stack, the project demonstrated proficiency in utilizing technology to drive actionable insights, align with strategic goals, and enhance support for African American communities.
PROJECT GALLERY
