Data Analysis ChatGPT: A 4-Step AI-Powered Framework for Business Analysts (Plus Real Netflix Case Study)

TL;DR: 📹 Watch the Complete Video Tutorial 📺 Title: Data Analysis with ChatGPT (in 4 steps), AI replacing analysts

• 📹 Watch the Complete Video Tutorial
• Why AI Won’t Replace Business Analysts—It Will Elevate Them
• The Four Pillars of Future-Proof Business Analysts
• Step-by-Step: The 4-Step AI-Powered Data Analysis Flow
• Step 1: Build a Learning Agenda (Your Strategic Compass)
• Step 2: Data Wrangling with AI (Clean Faster, Not Harder)
• Step 3: Visualize with Google Gemini (Native, Real-Time, Traceable)
• Step 4: Apply Human Judgment (Where Magic Happens)
• Advanced Data Storytelling: From Charts to Strategy
• Framer AI: A Bonus Tool for Analysts Who Also Design
• Framer’s AI-Powered Features
• The Role of Curiosity in Professional Evolution
• Real-World Application: Internship Success with AI
• Prompt Engineering Tips for Analysts
• Validation: How to Audit AI Outputs
• Tools Mentioned & Recommended
• Common Pitfalls to Avoid
• How to Start Today: Your Action Plan
• The Bigger Picture: Purpose Over Productivity
• Final Takeaway: Your Judgment Is Irreplaceable

In a world where AI tools are evolving faster than ever, business analysts face a critical question: Will AI replace me? The resounding answer from expert Lilian—a seasoned business analyst and educator—is a confident no. Instead, AI is a powerful ally that, when used intentionally, can dramatically accelerate your data analysis workflow while amplifying your uniquely human strengths.

In this comprehensive guide, we unpack Lilian’s proven four-step data analysis flow with AI, demonstrated using real Netflix 2024 revenue data. You’ll learn exactly how to integrate tools like ChatGPT and Google Gemini into your daily work—not to replace your expertise, but to enhance it. Plus, discover why emotional intelligence, critical thinking, and human judgment are now more valuable than ever.

We’ll also explore how platforms like Framer are revolutionizing creative workflows, and reflect on the deeper purpose behind professional identity in the age of automation.

Why AI Won’t Replace Business Analysts—It Will Elevate Them

Lilian opens with a personal reflection: during a break from her job in Vietnam, she found herself asking, “Who am I outside of my job?” This introspection led to a powerful realization: “When you’re goal-oriented, you chase. But when you’re purpose-driven, you expand.”

This mindset shift is crucial for analysts navigating AI. Rather than fearing obsolescence, the focus should be on incorporating AI into your current workflow with intention. AI doesn’t eliminate the need for business analysts—it redefines their role, placing greater emphasis on strategic thinking, storytelling, and human-centered judgment.

The Four Pillars of Future-Proof Business Analysts

Lilian identifies four key traits that will distinguish top-performing analysts in the AI era:

1. Emotional Intelligence: Understanding stakeholder motivations, decision-making styles, and how your work makes others feel.
2. Critical Thinking: Breaking down complex problems and knowing precisely where human insight is needed versus where AI can accelerate tasks.
3. Technical Fluency: The ability to structure clear, effective prompts and validate—or even challenge—AI outputs.
4. Human Judgment: Synthesizing data, strategy, and communication into narratives that align teams and drive action.

As Lilian puts it: “In functional business strategy, there’s no perfect strategy. There’s only a strategy your team feels most aligned with. And that’s why your voice and your judgment will always matter.”

Step-by-Step: The 4-Step AI-Powered Data Analysis Flow

Lilian demonstrates her framework using Netflix’s 2024 public financial data. This isn’t theoretical—it’s a real-world, actionable process you can replicate immediately.

Step 1: Build a Learning Agenda (Your Strategic Compass)

Before diving into data, create a learning agenda—a Google Doc containing 5–8 strategic questions to guide your analysis and prevent getting lost in noise.

When using ChatGPT to generate these questions, include these four critical elements in your prompt:

Pro Tip: Avoid specifying exact chart types (e.g., “bar chart”). Let Gemini choose the most effective visualization based on the data structure.

Step 2: Data Wrangling with AI (Clean Faster, Not Harder)

Instead of manually building pivot tables in Google Sheets, use ChatGPT to generate clean summary tables instantly.

Example Prompt:
“Summarize in a table: total revenue by region for each quarter of 2024.”

Once ChatGPT outputs the table:

1. Copy and paste it into a new tab in your Google Sheet.
2. Ensure formatting is consistent (e.g., currency, decimals).
3. Prepare for visualization by flattening complex structures into raw, editable text if needed.

This step transforms messy raw data into an analysis-ready format in seconds—freeing you to focus on interpretation.

Step 3: Visualize with Google Gemini (Native, Real-Time, Traceable)

Google Sheets now includes Gemini in the right-side panel. This integration is a game-changer because you can:

• Copy-paste prompts directly from your learning agenda.
• See exactly which cells Gemini references for each chart.
• Understand the logic behind visual choices in real time.

Example Workflow:

1. Open your cleaned data tab in Google Sheets.
2. Open Gemini sidebar.
3. Paste: “Visualize total revenue by region for each quarter of 2024.”
4. Gemini generates an appropriate chart (e.g., stacked bar or line chart).

This native integration eliminates context-switching and ensures data integrity.

Step 4: Apply Human Judgment (Where Magic Happens)

This is the most critical step—and where AI cannot replace you. Lilian uses her 5-second rule: “Can your audience understand this chart within 5 seconds and grasp its key insight?”

Using the Netflix revenue chart as an example, she made three strategic enhancements:

1. Bold Top Labels: Added clear headers like “Total Quarterly Revenue” to frame the narrative.
2. Contextual Annotations: Highlighted Q4 with a dashed outline and note: “Netflix consistently sees strong Q4 performance due to year-end seasonality.”
3. Strategic Color Focus: Used color to draw attention to the US & Canada region, which contributes the most revenue.

She then reinforced this insight with a supporting chart showing that US & Canada has contributed ~45% of Netflix’s total revenue since 2020.

Advanced Data Storytelling: From Charts to Strategy

Lilian didn’t stop at basic visualization. She elevated the analysis into a strategic framework using ARPU (Average Revenue Per User) data.

Instead of a standard bar chart, she created a 2×2 matrix that maps regions by:

• Monetization (ARPU) on the Y-axis
• Subscription Scale on the X-axis

This transformation—from raw data to actionable strategy—is the hallmark of an elite business analyst. AI generated the numbers; human judgment created the meaning.

Framer AI: A Bonus Tool for Analysts Who Also Design

While focused on data analysis, Lilian also highlights Framer’s new AI tools—especially valuable for analysts involved in dashboard or report design:

Framer’s AI-Powered Features

Best of all, these features are included in Framer’s free plan (1 site, custom domain, SSL, unlimited pages).

The Role of Curiosity in Professional Evolution

Lilian’s personal journey underscores a deeper truth: professional identity shouldn’t be confined to job titles. During her break, she reconnected with her younger self—“so curious, loved learning new things, so optimistic.”

She now structures her days into two chunks:

• Inspiration Time: Learning (e.g., AI integration)
• Creation Time: Teaching, filming, designing

Her advice: “What if I blend educational tips with lots of creativity?” This fusion—of knowledge and artistry—is where modern analysts can truly differentiate themselves.

Real-World Application: Internship Success with AI

Lilian is also developing a course: “Succeed at Your Internship with AI.” One key tip she shares: “Let the earnings report guide you. It’s the company’s playbook—how it got here and where it’s going.”

For new analysts or interns, studying public financial data (like Netflix’s) using her 4-step flow is a powerful way to demonstrate strategic thinking from day one.

Prompt Engineering Tips for Analysts

To maximize AI effectiveness, Lilian emphasizes structured prompting. Key principles:

• Be specific about the task: “Summarize in a table…”
• Define the output format: “Copy-paste ready for Google Sheets”
• Include business context: “Why is this important for Netflix’s 2024 strategy?”
• Leave room for AI judgment: Don’t over-constrain chart types or methods.

Validation: How to Audit AI Outputs

Never trust AI blindly. Lilian’s workflow includes built-in validation:

1. After ChatGPT generates a summary table, spot-check totals against raw data.
2. When Gemini creates a chart, verify the referenced cell ranges in the formula bar.
3. Ask: “Does this align with known business patterns?” (e.g., Netflix’s Q4 seasonality).

Tools Mentioned & Recommended

• ChatGPT: For learning agendas and data summarization
• Google Gemini (in Sheets): For native, traceable visualizations
• Google Sheets: Central hub for data, AI, and collaboration
• Framer: For analysts creating interactive reports or dashboards

Common Pitfalls to Avoid

Lilian’s experience reveals frequent mistakes:

• Skipping the learning agenda → leads to unfocused, reactive analysis.
• Over-automating storytelling → charts without context fail the 5-second rule.
• Ignoring stakeholder psychology → even perfect data won’t drive action if it doesn’t resonate emotionally.

How to Start Today: Your Action Plan

1. Pick a dataset (e.g., your company’s sales data or public financials like Netflix).
2. Create a learning agenda using Lilian’s 4-element prompt structure.
3. Use ChatGPT to wrangle and summarize.
4. Visualize in Google Sheets with Gemini.
5. Apply human judgment: annotate, reframe, and connect to strategy.

The Bigger Picture: Purpose Over Productivity

Lilian’s journey reminds us that tools like AI should serve our purpose, not define it. Whether you’re gaining weight happily at 44.4 kg, booking a photo shoot in your “creative era,” or filming tutorials in Vietnam—your curiosity is your compass.

As she says: “This last month, it’s about learning. Learning new things. Whether it’s a hobby, a skill—it all comes from this purpose of being curious.”

Final Takeaway: Your Judgment Is Irreplaceable

AI can process petabytes of data in seconds. But only you can:

• Ask the right questions
• Frame insights with empathy and context
• Turn numbers into narratives that inspire action
• Align teams around a shared strategy

So, to answer the original question: No, AI will not replace business analysts. But analysts who leverage AI with intention, curiosity, and human-centered judgment will thrive like never before.

Data Analysis ChatGPT: A 4-Step AI-Powered Framework for Business Analysts (Plus Real Netflix Case Study)

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