Welcome to my GitHub portfolio! Here, you will find a selection of projects showcasing my skills and experience in Data Analytics, Digital Marketing, and Coding. I am passionate about using data to drive insights and decision-making, and I aim to continue developing my expertise in this field.
Digital Marketing Strategy / Better Skin – Digital Marketing Plan
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Description: This academic group project focused on developing a complete digital marketing strategy for Better Skin, a genderless skincare brand. The plan covered the setup of an e-commerce store on Shopify, SEO and content strategy, Google Ads campaigns (Display, Video, Shopping), social media ads, email marketing automation, and performance analytics using Google Analytics.
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Key Skills: Digital Strategy, SEO, Paid Media, E-commerce, Email Marketing, Analytics & KPI Measurement
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Tools Used: Shopify, Google Ads, Facebook & Instagram Ads, Mailchimp, Google Analytics 4
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Project Highlights:
- Built a Shopify e-commerce store and created a visual identity targeting gender-neutral skincare users aged 23–34 in New York.
- Planned and executed full-funnel ad campaigns (Awareness, Consideration, Purchase, Repeat) using Google Ads and Meta Ads.
- Created automated email flows for welcome, birthday, cart recovery, and customer retention.
- Designed an SEO strategy based on keyword research using Ubersuggest, with implementation across the site.
- Measured key performance indicators such as website sessions, cart abandonment rate, traffic sources, and returning customers using GA4.
Google Analytics / Google E-Commerce Store
- Description: In this project, I analyzed e-commerce data using Google Analytics 4 to assess user behavior across landing pages, product performance, and the checkout funnel. By exploring key metrics such as purchase conversion rate, cart abandonment, and funnel drop-off points, I identified friction areas in the customer journey and proposed data-driven strategies to increase conversions.
- Key Skills Used: Data Interpretation
- Tools: Google Analytics 4
- Key Features:
- Identified a high checkout abandonment rate at the payment stage and proposed concrete UX and payment method improvements.
- Analyzed product-level cart abandonment rates, highlighting high-interest items like Google Stickers with low conversion follow-through.
- Evaluated landing page performance, revealing underperforming pages.
SQL, Python, Power BI / Mental Health in the Tech Industry
- Description: In this project, I explored survey data on mental health in the tech industry using SQL. The goal was to assess how professionals experience, discuss, and receive support for mental health issues at work. By organizing questions into thematic categories (e.g., diagnosis, benefits, stigma, company culture), I cleaned and analyzed the dataset to uncover trends and meaningful insights that can support employee well-being. I also combined Python and SQL to generate a custom Word Cloud from open-text responses, which was integrated into the Power BI dashboard to visually highlight the most frequent suggestions for improving support.
- Key Skills Used: Data Cleaning, SQL Queries, Data Categorization, Insight Extraction
- Tools: SQL Server Management Studio (SSMS), Power BI and Python
- Key Features:
- Cleaned and standardized survey responses across multiple question types (e.g., binary, Likert scale, open text).
- Grouped questions by theme to allow structured analysis across areas like employer support, diagnosis history, and employee comfort levels.
- Used SQL to calculate percentages, handle missing values, and identify patterns across survey years.
- Enabled a deeper understanding of mental health culture in tech environments based on real-world responses.
SQL, Excel, Power BI / Digital Music Store Analysis
- Description: This project focuses on analyzing data from a digital music store to uncover customer preferences, identify sales trends, and provide actionable insights for optimizing the music catalog. By leveraging SQL, I explored sales records, user ratings, and purchasing behavior across various genres and artists.
- Key Skills Used: Data Analysis, SQL, Data Visualization.
- Tools: Microsoft SQL Server, Excel, Power BI
- Key Features:
- Analysis of customer purchasing preferences by genre and artist
- Trend identification of top-selling music categories
- Data-driven recommendations to optimize the catalog and improve sales
- Visual dashboards and charts to support insights and facilitate decision-making
- Description: In this project, I am working on analyzing user adoption behavior for a fictional company, Relax Inc. The goal is to identify users who have adopted the platform based on login frequency and other factors. Using a Decision Tree model, I aim to predict whether a user will become an "adopted user".
- Key Skills Used: Data Cleaning, Exploratory Data Analysis, Data Mining, Predictive Analytics.
- Tools: Python.
Tableau, Excel / Google Trends Portugal Dashboard
- Description: This project consists of creating an interactive dashboard using data from Google Trends, focused on the most popular search queries in Portugal over a 7-day period. The goal is to provide a clear and visually engaging view of the most searched topics, enabling the identification of trends, relevant events, and patterns of public interest in Portugal.
- Tools used: Tableau, Excel
- Key Features:
- KPIs for total volume, top trends, and top trending search.
- Time-series chart showing daily volume distribution.
- Treemap illustrating the percentage share of each trend.
Google Looker Studio / Netflix Content Dashboard
- Description: Explore the interactive dashboard analyzing Netflix’s global catalog.
- Tools: Google Looker Studio, Google Sheet
- Key Features:
- Title trends over time.
- Movie vs TV Show distribution.
- Popular genres and ratings.
- Geographic breakdown of content.
- Programming Languages: Python, SQL
- Tools & Technologies: Power BI, Google Looker Studio, Tableau, Google Analytics, Excel
- Data Science: Data Preprocessing, Predictive Modeling, Data Visualization, Data Mining