Colin Miller

Data Analyst | Educator
Seattle, Washington USA
[email protected]

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• Tableau Public

About Me

I am a data analyst with a strong foundation in mathematics, problem-solving, and stakeholder collaboration. With five years of experience analyzing student performance data to inform instructional strategies, I have developed a keen ability to translate complex data into actionable insights.I’m excited to find a data analytics role where I can apply my technical expertise, analytical mindset, and problem-solving abilities to help organizations make informed, impactful decisions.If you want to talk about one of my projects, how my skills align with your company, or just want to connect, please reach out!
[email protected]
LinkedIn

Skills

Projects

Electrifying the Evergreen State

An Analysis of Electric Vehicle Adoption and Charging Infrastructure in Washington State

Tools Used: Excel (Data Cleaning, Integration, Calculations), Tableau (Data Visualization, Geographic Analysis)In this project, I analyzed Washington State’s electric vehicle (EV) landscape using publicly available datasets to support equitable, data-driven infrastructure planning. Using Excel, I cleaned and integrated EV registration data, population estimates, charging station locations, and ZIP-to-county mapping. I applied functions like V/XLOOKUP, COUNTIF, SUMIF, and PERCENTOF to create a consolidated dataset for analysis. I then visualized key findings in Tableau, highlighting:🚗 EV Adoption Patterns – Total and per-capita EV ownership across Washington counties
🔌 Charging Infrastructure Adequacy – Ratios of EVs per station and per port to identify high-competition regions
🌄 Charging Deserts – Underserved areas based on both population size and geographic coverageBased on the analysis, I recommended a targeted approach to infrastructure expansion: invest in high-population counties like Pierce and Snohomish with strong growth potential, reduce charger congestion in areas with strained infrastructure such as Snohomish, Mason, Island, and Klickitat counties, address rural coverage gaps across 31 counties falling below EPA standards, and improve spatial equity in dense EV hubs like King County by optimizing charger distribution rather than simply increasing quantity.View my Excel file or view in Google Sheets

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• Infrastructure Dashboard
• EV Types Dashboard

Bellabeat Case Study

Tools Used: SQL (Google BigQuery), Tableau (Interactive Dashboards, Data Storytelling)For this project, I analyzed smart device fitness data to uncover trends in consumer behavior and provide data-driven marketing insights for Bellabeat, a health-focused tech company. Using SQL, I cleaned, transformed, and merged user activity, sleep, and weight data, preparing it for further analysis. Key findings were visualized in Tableau, highlighting:👟 User Activity Patterns – Trends in step counts and movement habits
💤 User Sleep Patterns – Trends in sleep over the course of the week
🤓 Sleep & Activity Correlations – Identifying relationships between sleep duration and physical activityBased on these insights, I recommended strategic initiatives, such as personalized step goals, morning push notifications for device use, optimized sleep reminders, and targeted messaging on sleep’s impact on activity. These data-driven strategies help Bellabeat refine their product experience and better connect with their target audience in the global smart device market.

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15 Day SQL Challenge

I recently finished a 15-Day SQL Challenge hosted by PrepVector!✅ 15/15 days completed
🏅 Score: 134/150
📊 Rank: 87 out of 1,619 participantsThroughout the challenge, I tackled real-world business problems that spanned across industries. Some of my favorite challenges included:➕Multi-Day Customer Counts
💰Product Sales by Month
🔥User Consecutive Day Streaks
📈Monthly Revenue Growth
🚫Detecting Duplicate TransactionsAlong the way, I strengthened several key SQL skills and strategies:💡 Understanding the importance of clarifying business logic. Some problems only made sense once I researched terminology or reframed the question
💡 Thinking critically about data structure, assumptions, and how to write efficient, readable queries
💡 Combining COUNT with CASE WHEN to count specific conditions or categories within grouped data
💡 Writing self-joins by aliasing a table to compare rows within the same dataset
💡 Applying window functions like RANK(), DENSE_RANK(), and LAG() to analyze trends over time and identify patterns between rows

• See my work!

9th Grade Student Performance Analysis

Tools Used: Excel (VLOOKUP, Conditional Formatting, COUNTIF(S), Charts)For this project, I analyzed real classroom data to uncover trends that support student success. Using Excel, I merged gradebook data for 100+ students across four core subjects, improving data accessibility and reporting. Key analyses included:✅ Gradebook Integration – Used VLOOKUP to consolidate student records from multiple subjects
✅ Performance Categorization – Applied conditional formatting and COUNTIF(S) to identify academic trends
✅ Grade & Attendance Insights – Used scatterplots and linear regression to explore relationships between GPA, subject performance, and attendance
✅ Data-Driven Decision Making – Provided insights to stakeholders to support targeted student interventions and pedagogical reflectionsDue to the sensitive nature of this data, I’m unable to share the files. However, I’d love to discuss my findings and analytical techniques—feel free to reach out!

Toy Car Sales Dashboard

Tools: Excel (Pivot Tables, Charts, Dashboards, Slicers)For this project, I analyzed a sample sales dataset from Kaggle, which includes transactional data such as product sales, territories, and shipment statuses. Using Excel Pivot Tables, I aggregated key insights and developed an interactive dashboard that visualizes:
✅ Top 5 Products by sales performance
✅ Sales by Territory to identify regional trends
✅ Sales Over Time to track revenue patterns
✅ Shipment Status breakdown for logistics insights
✅ Sales by Country for market segmentationTo enhance usability, I incorporated slicers for interactive filtering, allowing users to dynamically explore the data. This project strengthened my ability to analyze business trends, create data-driven visualizations, and build user-friendly dashboards.The Sample Sales Data is made public by Gus Segura on Kaggle.🔗 View my dashboard in Excel or a photo here

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