Data Analytics - Work Portfolio
My portfolio showcases a diverse range of successful projects, highlighting my expertise in data analysis, project management, and innovative solution development across various industries
Optimizing Performance: Developing KPIs for a Fintech Company
The project's objective was to create a dynamic Business Analytics Dashboard for a Fintech company, providing deep insights into vital KPIs such as topline growth, new customer acquisition, and churn rates, using Azure Data Lakes for data storage, Power Query for data transformation, and Power BI for robust data visualization. The dashboard featured complex DAX modeling for nuanced KPI analysis, real-time insights on customer attrition patterns and market reception of new products, and a user-friendly interface for efficient navigation and analysis of business metrics, particularly focusing on tracking business gained from new customers and losses.
Global Viewership & Hreflang Analysis Dashboard via Google Data Studio
The project aimed to create a Google Data Studio Dashboard for tracking and analyzing digital marketing metrics across multiple countries, focusing on Hreflang tag implementation and circumventing regional web blockades. Key challenges included integrating Google Analytics data, ensuring real-time accuracy, and providing insights into country-specific engagement, traffic, SEO, and content performance. The dashboard featured global traffic analysis, Hreflang tag tracking, user engagement metrics, real-time data visualization, and localized content performance analysis. Outcomes included data-driven decision-making, an expanded global online presence, and enhanced SEO performance, particularly in navigating regional website blockades.
Evaluating the Business Impact of Customer Reviews: A Data-Driven Approach to Purchasing Trends Analysis
The project aimed to understand the impact of customer ratings on the monetary value of purchases within an enterprise. It involved a detailed data exploration and analysis using various statistical techniques such as correlation analysis, decision tree frameworks, and multivariate regression. Key insights included:
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Minor Direct Correlation: Analysis indicated a slight relationship between Attend Poll Ratings and purchase amounts, suggesting no direct strong link between customer ratings and spending.
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Decision Tree Model Insights: This non-linear model showed that certain rating brackets correlate with specific average purchase amounts but could explain only about 7.15% of the variance in spending based on ratings.
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Multivariate Analysis: Incorporated variables like Advisor Names and Program Types, converted into numerical formats via one-hot encoding. The analysis revealed that each unit increase in Attend Poll Rating, while keeping other variables constant, was associated with a $3.22 increase in purchase amount.
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Decision Tree Regression: Accounted for a significant 77.04% of variance in expenditures, highlighting the complex interplay between Attend Poll Ratings, Advisor Names, Program Types, and spending. It identified certain advisors and programs with strong correlations, suggesting their influence on customer feedback.
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Identification of Key Contributors: The analysis pinpointed top advisors and program types that contributed to 80% of the ratings, providing valuable insights for targeted business strategies.
User Engagement and Loyalty Analytics Dashboard for Enhanced User Retention
This project developed an analytics dashboard to enhance user stickiness and loyalty for a digital platform, aiming to improve user retention and engagement. It involved categorizing user metrics for nuanced behavior analysis, examining the retention lifecycle, and tracking session lengths to assess engagement. The project also analyzed different user segments (returning, dormant, and new users) and developed targeted conversion strategies. Additionally, it focused on user journey mapping and curated metrics for editorial insights to tailor content and marketing strategies. The resulting dashboard offered valuable insights into user behavior, significantly aiding in decision-making to boost user retention and engagement.
The successful implementation of this dashboard led to a deeper understanding of user behavior, enhanced user loyalty, and improved retention rates, contributing to a more engaging user experience and a stronger user base.
Real-Time Log Monitoring and Error Analysis
In this project, we developed a comprehensive Power BI dashboard for a FinTech company to monitor operational metrics like log reports, error rates, and performance indicators. Key aspects included integrating Azure Data Lakes for robust data aggregation, utilizing Power BI for advanced data visualization, and creating multiple interactive visualizations for varied operational aspects. We focused on detailed operational metrics, employing complex DAX modeling and SQL for data transformation. The outcome was an insightful, real-time dashboard that empowered decision-makers to quickly identify and address operational challenges, optimize performance, and facilitate strategic, data-driven decisions.
Project Management Performance Tracker with Risk Profiling
The project developed an Advanced Project Management Tracker using Microsoft Azure and JIRA, focusing on key metrics like CPI, EV, PV, and AC, and featured risk profiling for effective oversight. With PowerBI dashboard visualizations and Power Apps alert systems, it enhanced project control and resource utilization. Techniques included API integration with JIRA for seamless data extraction and real-time sync, ensuring up-to-date information. This comprehensive tool significantly improved decision-making, optimized resource management, and mitigated risks, leading to successful project outcomes.
