How I Apply What I Learn
I believe the best way to understand technology is through hands-on practical application. I use ChatGPT to run focused 15-minute micro-learning lessons that allow me to quickly learn, test, and apply new concepts in real time. These projects reflect how I’ve strengthened operational systems, contributed to technology adoption, and continue advancing my analytical and AI capabilities through real-world and self-directed application to drive smarter business decisions.
I had three separate learning plans - SQL, Excel, and Power BI - with zero connection between them.
That's not how the job works.
So I built the Analyst Accelerator: one system, one dataset, three tools working in sequence. SQL extracts and validates the raw data. Excel builds the analysis model. Power BI turns it into an executive dashboard.
Every 15-minute session follows the same structure: Teach, Apply, Evaluate, Advance - with Claude AI as the coaching layer throughout.
The output isn't three separate skills. It's one portfolio project that tells a complete analyst story from raw data to published dashboard.
Below you will find
Program overview presentation.
Master prompt that you can use yourself, or ask AI to customize it to whatever you want to learn.
Two-slide example of Day 3 of my SQL AI Analyst Accelerator below. I built a regional performance breakdown from 8,800 rows of real data from Maven Analytics - data playground.
West leads in revenue. East wins on efficiency. Central works the hardest and gets the least return per deal.
"What is this actually costing me?" full tech stack. The only thing this portfolio cost me was $20/month and a decision to start.
AI Adoption Is Being Pushed Across Companies - But Leaders Are Learning It Too. Here’s How They Can Use It for Strategic Decisions.
AI is now embedded in tools companies already use. The gap isn't access - it's knowing how to use it for decisions that actually matter.
In this project, I demonstrate how an AI agent can function as an Executive Decision Analyst: structuring analysis, comparing options, surfacing risks, and pressure-testing assumptions so leaders can make more informed decisions.
My Background on This
At Verizon Business, I served on the AI Automation & Adoption Pillar team. My work had two sides: driving adoption across operational teams through enablement and change management, and researching how other companies were applying AI - then bringing those insights directly to AVP-level leadership to inform innovation priorities, investment decisions, and strategic direction.
That exposure shaped how I think about AI in a strategic context. This project brings that mindset into a hands-on demonstration.
What the Demo Shows (video below)
An AI agent helping a leader:
Compare strategic options
Identify risks and opportunities
Account for adoption and compliance realities
Explore innovation scenarios
Not to make the decision - to support it.
Starter Prompt (Word doc below - click the expand icon in the bottom-right to open)
The exact prompt used in the video, available for anyone to try.
The Takeaway
AI agents don't replace leadership judgment. They offload the analysis behind decisions so leaders can focus on strategy, direction, and execution.
Built using ChatGPT Agent Mode. AI also supported post-production - analyzing the recording and recommending edits. That's the point: AI doesn't just support business analysis. It supports how we think and communicate.
Power BI Capstone: Turning Raw Data Into Decisions (Video walkthrough below)
Executives don't ask "Can you build me a dashboard?" They ask:
Are things getting better or worse?
Where should we focus?
What do we need to prepare for?
This dashboard was built to answer those questions — not just display numbers.
What It Visualizes
Total case trends over time
Daily new case volatility
Growth rate acceleration and slowdowns
Interactive filtering by country and time
My Role
I independently designed and built this as a Capstone project for my edX upskilling course - from structuring the dataset to building the visuals to recording the walkthrough. I used ChatGPT micro-learning lessons throughout to deepen my understanding as I built.
The Takeaway
The value of analytics isn't the dashboard. It's whether a leader can look at it and immediately understand what's happening, why it matters, and where to focus next. That was the standard I built to.
Note: Due to publishing limitations, this is demonstrated via recorded walkthrough rather than a live embedded report. In a production setting, users would interact directly with the front-end interface.
Power BI Sales Dashboard and Data Visualization Project
Objective: Develop hands-on experience building dashboards to visualize business data and provide performance insights.
My Role: Using sample sales and operational datasets through ChatGPT 15-minute micro learnings to build dashboards that track performance trends, identify patterns, and improve data storytelling. The emphasis is on designing reports that transform data and deliver actionable understanding in a practical business context.
The first video captures the project in progress - before SQL was complete and Power BI had begun. The second video is the finished dashboard, built across all three layers: SQL, Excel, and Power BI.
Impact: This work continues to reinforce the importance of clear visualization, thoughtful data structure, and focusing analytics on answering real organizational questions.
