ChatGPT for Data Analysis in Excel: Case Study | Course Module скачать в хорошем качестве

ChatGPT for Data Analysis in Excel: Case Study | Course Module

For analysts in 2026, AI is no longer just a chatbot. It’s a powerful data analysis partner. In this course preview, we explore how to leverage ChatGPT to clean messy data sets, write complex Excel formulas, and provide domain-specific insights that would otherwise take hours of research. Learn how to interact with ChatGPT as a Senior Analyst. You’ll see how to pass raw tables from Excel into AI to identify "hidden" problems, such as surging inventory levels or inconsistent revenue units. We also dive into industry-specific metrics like RevPASH for restaurants, showing how AI can bridge the gap between raw numbers and professional business intelligence. In this lesson, you’ll learn how to: 🔷 Clean & Format Data: Use AI to instantly convert units (e.g., thousands to dollars) and fill in missing data points. 🔷 Generate Excel Formulas: Pass your cell references to ChatGPT to receive perfectly structured formulas for metrics like Inventory Turnover. 🔷 Identify Data Anomalies: Use AI to spot high-priority issues, such as dramatic rises in ending inventory, that may indicate operational risks. 🔷 Acquire Domain Knowledge: Ask ChatGPT to explain specialized industry metrics (like RevPASH) and provide benchmark data for comparison. 🔷 Perform Exploratory Data Analysis (EDA): Learn how to upload files so ChatGPT can write and execute Python code to analyze your data internally. 🔷 Extract Action Items: Move from "what the data says" to "what we should do" by asking the AI to prioritize investigation steps. The AI-Enhanced Analysis Workflow 1. Extract: Copy raw data directly from your Excel spreadsheet. 2. Interpret: Ask ChatGPT to place the data into a structured table to ensure it understands the context. 3. Audit: Use the AI to write formulas for specific columns, then paste them back into Excel to verify results. 4. Analyze: Role-play with the AI (e.g., "Act as a Senior Inventory Analyst") to gain high-level strategic insights. Pro Tip: Interacting with Large Language Models (LLMs) means everyone gets slightly different results. The goal isn't just to get an answer, but to experiment with prompts to see how the AI can help you clean, interpret, and visualize data more effectively. Mastering ChatGPT for data analysis enables you to spend less time on manual data entry and more time on high-value, strategic thinking. Topics Covered: 🔷 Cleaning Messy Data Sets with AI 🔷 Formula Generation and Cell Referencing 🔷 Inventory & Revenue Analysis Case Studies 🔷 Industry Benchmarking (High-end vs. QSR) 🔷 Introduction to Python for Analysis in ChatGPT 🔷 Prioritizing Business Issues using AI Logic #ChatGPT #DataAnalysis #AI #ExcelTips #BusinessIntelligence #InventoryManagement #FinancialAnalysis #PromptEngineering #CFI #Python