Rushikesh Shejul

Track A - Cyclistic Bike-Share Analysis

• Completed the Google Data Analytics Capstone Track A case study analyzing Cyclistic's historical bike trip data to identify trends between casual riders and annual members.
• Applied the complete data analysis process: defined business tasks (Ask), imported real datasets (Prepare), cleaned inconsistencies like duplicates and nulls (Process), identified usage patterns, such as ride duration peaks (Analyze), created visualizations in Tableau/Excel (Share), and recommended targeted marketing strategies to convert casual users (Act).
• Performed exploratory data analysis using SQL queries, spreadsheets, and R for statistical summaries; documented findings with charts showing member versus casual rider differences during peak hours and longer average trips.
• Delivered a portfolio-ready presentation with actionable insights for stakeholders, demonstrating junior data analyst skills for job interviews.

Track B - Custom Dataset Analysis.

• Executed the Google Data Analytics Capstone Track B by independently selecting a public dataset from Kaggle/data.gov on a topic of interest (e.g., Bitcoin trends or housing data), defining original business questions, and identifying stakeholders.
• Followed the Ask-Prepare-Process-Analyze-Share-Act framework: sourced and imported data, documented cleaning steps for outliers and merges using spreadsheets/SQL, and derived custom insights via trend analysis and metrics creation.
• Utilized tools including Python, R, and Tableau for visualizations; explored inspirations from Medium, GitHub, and Kaggle to develop self-directed analysis on investment viability or policy impacts.
• Produced an original case study with key findings, strategic recommendations, and a stakeholder summary, showcasing initiative and advanced, self-motivated data analytics capabilities for my resume/portfolio.

Tailwind Traders:

• Led an end-to-end business intelligence capstone project for Tailwind Traders to convert raw transactional data into executive-level sales and profit insights using Excel and Power BI.
• Prepared and cleansed sales data in Excel by creating Gross Revenue, Total Tax, and Net Revenue columns, validating calculations, and ensuring data accuracy for analysis.
• Configured multiple data sources in Power BI (Sales, Purchases, Countries, Exchange Rates) by loading Excel files, setting correct data types, and profiling column quality to maintain data integrity.
• Designed a snowflake data model by defining relationships between Sales, Purchases, Countries, Calendar, and Exchange Data tables to support flexible analytical queries.
• Built DAX-based calculated tables and measures, including a Calendar table and a 'Sales in USD' table, to standardize global sales and profit figures into U.S. dollars, and enable time-intelligence reporting.
• Developed interactive analytical reports with KPIs, cards, bar/column charts, line and area charts, and pie/donut charts to show revenue, quantity sold, tax, and profit trends by country, product, and time.
• Created an executive dashboard in Power BI Service (Tailwind Traders Executive Dashboard), and pinned key report visuals to provide a consolidated view of global performance for stakeholders.
• Implemented alert rules (for example, Gross Revenue USD below a defined threshold), and report email subscriptions (weekly Sales and Profit summaries) to automate monitoring and stakeholder notifications.
• Optimized reports and dashboards for mobile devices by configuring a dedicated mobile layout and arranging critical KPIs and visuals for quick, on-the-go decision-making.
• Documented steps, assumptions, and best practices followed in data preparation, modeling, and visualization to ensure the project is reproducible and aligned with industry-standard BI practices.

• Resolved customer complaints in a timely manner by providing appropriate solutions or alternatives.
• Created reports on system performance metrics using various analytical tools.
• Supported the team in executing daily operational tasks.
• Coordinated communication between departments to streamline workflow processes.
• Performed root cause analysis on incidents reported by customers.
• Provided training and mentoring for junior staff members on CAP systems.