Tableau - Google Fiber Dashboard 

For my final project in the Google Business Intelligence Certificate program, I designed a dashboard that centers on client interactions at Google Fiber. The goal was to evaluate the efficacy with which agents handled customer issues on their first call, intending to lessen the instances of repeated calls for the same concern.

A deep dive into Google Fiber's customer service data reveals that Market 1 consistently stands out with the greatest volume of recurring calls. This underscores a pressing need to enhance communication or service quality in this sector. Notably, Issues labeled as Types 2 and 5 are the main culprits for these repeat engagements. Over the course of a typical week, Monday sees a surge in call volumes, while Sundays witness a significant drop, suggesting potential service queries following the weekend. Problem Type 5 deserves special attention; not only does it lead to a large number of initial repeat calls, but it frequently remains unaddressed after the first engagement.

For the purpose of this demonstration, I created and used dummy data to showcase the SQL script that consolidates data from various sources to deliver a detailed monthly financial risk assessment. It facilitates strategic decision-making by offering in-depth insights into user behavior and financial metrics, segmented by user-specific attributes. 

Beyond its technical aspects, this script symbolizes my personal journey as a Risk Analyst. Despite not having formal training in SQL, I embraced the challenge of teaching myself, driven by a strong desire to contribute meaningfully to my role. The result is a tool that not only provides valuable insights for strategic decision-making but also underscores the profound impact of determination, continuous learning, and a love for data.

I crafted a dashboard using mock data related to P&G Company's sales. The dashboard's purpose is to deliver a panoramic view of the company's sales trends, diving into specifics like sales by category, monthly sales breakdowns, as well as comparing actual sales and forecasted figures for the year. With this comprehensive insight, stakeholders can swiftly pinpoint top-performing and underperforming products, thus enabling data-driven decisions.

I created a dashboard for my student client by first studying the dataset to understand its structure and key variables. I then built a data model to support the dashboard, ensuring that the relationships between tables were accurate and optimized for analysis. After developing the visualizations, I explained the entire process to the client from data preparation to dashboard creation and provided a comprehensive analysis of the findings.

This dashboard, created from tutorials, gives a detailed analysis of UK road accidents. This comprehensive tool not only tracks accidents but dives deep into their nuances, offering detailed insights. The overarching goal of this dashboard is to serve as a data-driven foundation upon which the government can formulate effective and informed road safety policies.