AI How-To's & Tricks
ChatGPT for Data Analysis: The Ultimate Guide to Unlocking Insights

We all work with data, but very few of us were ever formally taught how to analyze it in a structured, effective way. This often leads to hours wasted trying to make sense of complex spreadsheets. But what if you could turn that confusion into clarity in a matter of minutes? This guide will show you how to use ChatGPT for data analysis, transforming the powerful AI into your personal data analyst—no technical skills required.
By leveraging a simple yet powerful three-step framework, you can bridge the gap between raw data and meaningful insights. This method helps you understand new datasets faster and extract insights that, as a non-data analyst, you might have otherwise missed. Let’s get started!

Table of Contents
- The DIG Framework: Your Secret Weapon for Data Analysis with ChatGPT
- Step 1: Description – Getting ChatGPT to Understand Your Data
- Step 2: Introspection – Brainstorming Questions and Possibilities
- Step 3: Goal Setting – Guiding the AI Towards Your Objective
- Key Takeaways for Mastering ChatGPT Data Analysis
The DIG Framework: Your Secret Weapon for Data Analysis with ChatGPT
The core of this technique is a framework called DIG, which stands for Description, Introspection, and Goal Setting. It’s a simplified version of the industry-standard process known as Exploratory Data Analysis (EDA), but it’s much easier to remember and apply. By feeding ChatGPT prompts based on the DIG framework, you systematically build a comprehensive understanding of any dataset.
Think of it like this: when you receive a new spreadsheet, your understanding is at 0%. With each DIG prompt you use, that understanding increases, until you’ve uncovered meaningful insights that would have taken hours to find manually—if you found them at all.
Step 1: Description – Getting ChatGPT to Understand Your Data
The first step is all about getting ChatGPT to describe the data file as quickly and effectively as possible. This lays the foundation for all subsequent analysis. To do this, simply upload your CSV or Excel file to ChatGPT (this requires a Plus subscription) and start with these powerful prompts.
Description Prompt #1: Get a Column Overview
This initial prompt forces ChatGPT to scan every column and give you a high-level summary.
List all the columns in the attached spreadsheet and show me a sample of data from each column.
This is crucial because it gives you a quick, digestible overview instead of overwhelming you with the entire spreadsheet. It also immediately highlights the data formats in each column, helping you spot potential issues, such as multiple genres being listed in a single cell or a release year having a decimal point.
Description Prompt #2: Spot Inconsistencies with More Samples
A single sample might be an outlier. To get a more accurate picture, you need to look at more data.
Take 5 more random samples of the data for each column to make sure you understand the format and type of information in each column.
This helps you confirm patterns and spot inconsistencies. For example, you might see that some titles have one genre while others have three, or that a title is available in one country while another is available in multiple.
Description Prompt #3: Run a Data Quality Check
Now, let’s have ChatGPT explicitly look for problems. This is one of the most powerful tricks when using ChatGPT for data analysis.
Run a data quality check on each column. Specifically look for:
- Missing, null, or empty values (give me counts and percentages)
- Unexpected formats or data types
- Outliers or suspicious values
This prompt is designed to find red flags. In the video’s example, this revealed that 99.7% of the data was missing for the “availableCountries” column, making any geographical analysis on that dataset completely unreliable. Discovering this early saves you from pursuing a dead end.
Step 2: Introspection – Brainstorming Questions and Possibilities
Once you and ChatGPT have a solid grasp of the data’s structure and quality, the next step is to brainstorm. The goal here is to instruct ChatGPT to think about what the data can and, just as importantly, *cannot* tell you. This tests whether the AI truly “gets” your data and often surfaces insights you hadn’t considered.
Introspection Prompt #1: Generate Insight-Rich Questions
Tell me 10 interesting questions we could answer with this dataset and explain why each would be valuable.
If ChatGPT generates good, relevant questions, it’s a sign that it understands the dataset’s potential. If the questions are poor, it indicates a misunderstanding that needs to be corrected before proceeding. This prompt can spark ideas for your analysis that you might not have thought of on your own.
Introspection Prompt #2: Identify Data Gaps
This is my personal favorite prompt in this section because it manages expectations and prevents you from overpromising.
What questions do you think someone would WANT to ask about this data but we CAN’T answer due to missing information?
This surfaces the limitations of your dataset. For instance, you might want to know the most-watched genre, but if your data lacks viewership metrics, you can’t answer that. Knowing this upfront allows you to inform your boss or stakeholders about what insights are possible and what additional data might be needed. For more powerful analysis, you can often find supplementary data on platforms like Kaggle and merge it with your original file.
Step 3: Goal Setting – Guiding the AI Towards Your Objective
Analyzing data without a clear goal is like driving without a destination—you’ll burn a lot of fuel but end up nowhere useful. This final step is about giving ChatGPT a clear mission briefing so it can prioritize its analysis and deliver results that are directly relevant to your objective.

Instead of a vague request, give ChatGPT a specific goal:
My goal is to understand what content Apple TV should invest in next. Given this goal, which aspects of the data should we focus on?
This prompt helps the AI prioritize what’s important (like unit economics, audience demand, and content supply) and ignore what’s not. The result is a practical, step-by-step roadmap tailored to your specific objective, turning a massive dataset into a clear action plan.
Key Takeaways for Mastering ChatGPT Data Analysis
This entire process is designed to be a simple, repeatable system that anyone can use immediately. Here are two final things to remember:
- The DIG framework levels the playing field. You no longer need to be a formally trained data scientist to derive powerful insights from data. This process empowers any professional to work smarter. For more tips like this, check out our other AI How-To’s & Tricks.
- This is just the beginning. While this guide covers the essentials, there’s always more to learn. The video’s creator learned this framework from a Coursera course that delves deeper into topics like mitigating AI hallucinations and debugging data errors.
By using ChatGPT for data analysis with a structured framework, you can save time, uncover hidden insights, and make smarter, data-driven decisions in your role.
Watch the full video walkthrough here:(6) Master Data Analysis with ChatGPT (in just 12 minutes) – YouTube
AI How-To's & Tricks
Google Translate Hidden Features: Discover This Powerful Workflow

If you’re a language teacher or a dedicated student, you probably use Google Translate regularly. But are you using it to its full potential? Many users are unaware of several Google Translate hidden features that, when combined, create an incredibly efficient and powerful workflow for language acquisition. This guide will reveal a three-step process that transforms how you find, save, and practice new vocabulary, turning passive translation into active learning.

Step 1: Save Translations to Create Your Custom Phrasebook
The first hidden feature is simple yet foundational: the ability to save your translations. Every time you translate a word or phrase that you want to remember, don’t just copy it and move on. Instead, look for the star icon next to the translated text.
Clicking this “Save translation” star adds the entry to a personal, saved list within Google Translate. You can access this growing collection of vocabulary and phrases anytime by clicking on the “Saved” button at the bottom of the translation box. This allows you to build a curated phrasebook of the exact terms you’re focused on learning, all in one place.
Step 2: Find Authentic Language with YouTube Transcripts
To make your learning effective, you need authentic content. YouTube is a goldmine for this, and another trick makes it easy to integrate with Google Translate. You can find real-world conversations, podcasts, and lessons on any topic in your target language.
Here’s how to leverage it:
- In the YouTube search bar, type your topic and add the language (e.g., “shopping in English” or “cooking in Polish”).
- Click the “Filters” button and select “Subtitles/CC”. This ensures all search results are videos that have a transcript available.
- Once you find a video, play it. Under the video description, click the “…more” button and scroll down until you see the “Show transcript” option.
- The full, time-stamped transcript will appear. Now you can easily highlight, copy, and paste any sentence or phrase directly into Google Translate to understand its meaning and save it to your phrasebook from Step 1!
This method is one of many powerful techniques you can explore in our AI How-To’s & Tricks section.
Step 3: The Magic Button – Export to Google Sheets
This is one of the most powerful Google Translate hidden features that connects everything. Once you’ve built up your “Saved” list of vocabulary, how do you get it out of Google Translate to use elsewhere? With the magic “Export” button!
In your “Saved” translations panel, look for the three vertical dots (More options) in the top right corner. Clicking this reveals an option: “Export to Google Sheets.”

With a single click, Google will automatically create a new Google Sheet in your Drive, perfectly formatted with your source language in one column and the translated language in another. This simple export function is the key that unlocks endless possibilities for practice.
Bonus Tip: Turn Your Vocabulary List into Interactive Games
Now that your custom vocabulary list is neatly organized in a Google Sheet, you can easily import it into popular language learning tools to create interactive games and flashcards.
Two fantastic platforms for this are:
- Quizlet: Visit the Quizlet website to learn more. Quizlet has a direct import function. Simply copy the two columns from your Google Sheet, paste them into Quizlet’s import box, and it will instantly generate a full set of flashcards. From there, you can use Quizlet’s various modes like Learn, Test, and Match to practice your new words.
- Wordwall: [External Link Suggestion: Check out the activities on the Wordwall website.] Similarly, Wordwall allows you to paste data from a spreadsheet to create engaging classroom games like Match up, Anagrams, and Quizzes in seconds.
By following this workflow, you can go from watching an authentic YouTube video to playing a custom-made vocabulary game in just a few minutes. This is a game-changer for making language learning more efficient, personalized, and fun.
AI How-To's & Tricks
AI Job Displacement: Unveiling the Ultimate Threat to Your Career

The debate around AI job displacement is heating up, with conflicting headlines leaving many confused. On one hand, some reports promise a net increase in jobs; on the other, top industry insiders are sounding the alarm. An ex-Google executive calls the idea that AI will create new jobs “100% crap,” while the CEO of Anthropic reaffirms his warning that AI will gut half of all entry-level positions by 2030. So, what’s the real story? The data reveals a complex and disruptive picture that isn’t about the total number of jobs, but rather a massive shift in which jobs will exist—and who will be left behind.

The “100% Crap” Verdict from an Ex-Googler
Mo Gawdat, a former chief business officer at Google X, doesn’t mince words. He states that the widely circulated idea of AI creating a plethora of new jobs to replace the old ones is simply “100% crap.” His argument is grounded in the sheer efficiency of AI. He provides a stark example from his own startup, where an application that would have once required 350 developers was built by just three people using modern AI tools.
This isn’t a case of one job being replaced by another; it’s a case of hundreds of potential jobs being eliminated by a massive leap in productivity. According to Gawdat, even high-level executive roles, including CEOs, are at risk as AI-powered toolchains begin to automate complex decision-making and management tasks.
Anthropic CEO’s Dire Warning for Entry-Level Jobs
Adding to this concern is Dario Amodei, the CEO of AI safety and research company Anthropic. He has consistently warned that the most immediate and severe impact of AI will be felt at the bottom of the corporate ladder. He reaffirms his prediction that AI could wipe out half of all entry-level, white-collar jobs within the next five years.
Amodei points to specific roles that are highly susceptible to automation:
- Law Firms: Tasks like document review, typically handled by first-year associates, are repetitive and perfect for AI.
- Consulting & Finance: Repetitive-but-variable tasks in administration, data analysis, and financial modeling are quickly being taken over by AI to cut costs.
He argues that governments are dangerously downplaying this threat, which could lead to a significant and sudden spike in unemployment numbers, catching society unprepared.
Deceptive Data? What the World Economic Forum Really Says
At first glance, a recent report from the World Economic Forum (WEF) seems to offer a comforting counter-narrative. The headline projection is a net employment increase of 7% by 2030. Good news, right? Not exactly.
When you dig into the actual data, the picture becomes much more turbulent. The report projects that while 170 million new jobs will be created, a staggering 92 million jobs will be displaced. This represents a massive structural labor market churn of 22%.

This means that while the total number of jobs might grow, tens of millions of people will see their current roles vanish. The crucial question is whether the people losing their jobs will be qualified for the new ones being created.
The Great Divide: Growing vs. Declining Jobs
The WEF data highlights a clear and worrying trend. The jobs that are growing are not the same as the ones that are disappearing.
Top Fastest-Growing Jobs:
The roles with the highest projected growth are almost exclusively in high-tech, data-driven fields:
- Big Data Specialists
- FinTech Engineers
- AI and Machine Learning Specialists
- Software and Applications Developers
- Data Analysts and Scientists
Top Fastest-Declining Jobs:
Conversely, the jobs facing the steepest decline are the very entry-level, white-collar roles that have traditionally been a gateway to a stable career:
- Postal Service Clerks
- Bank Tellers and Related Clerks
- Data Entry Clerks
- Administrative and Executive Secretaries
- Accounting, Bookkeeping, and Payroll Clerks
This data directly supports the warnings from Amodei and Gawdat. The new jobs require advanced, specialized skills in AI and data science, while the jobs being eliminated are those that rely on codified, repetitive tasks that AI excels at automating.
The Productivity Paradox and the “Canary in the Coal Mine”
Economists and experts like Ethan Mollick are observing a pattern in macro data: unexpected decreases in employment are occurring alongside increases in productivity. While it’s too early to draw firm conclusions, Mollick notes this is exactly the pattern one would expect if AI were the cause. Companies can produce more with fewer people, leading to a productivity boom that doesn’t translate into broad job growth.
A recent Stanford study titled “Canaries in the Coal Mine” reinforces this, finding that early-career workers (ages 22-25) in the most AI-exposed jobs have already seen a 13% relative drop in employment compared to their less-exposed peers. This is happening even while overall employment is rising. The “canaries”—the youngest and most vulnerable in the workforce—are already feeling the effects.
Conclusion: The Future of Work is a Skill, Not a Job
The evidence strongly suggests that while AI may not lead to mass unemployment across the board, it will cause severe AI job displacement in specific, crucial sectors. The idea of a simple one-for-one replacement of old jobs with new ones is a dangerous oversimplification. The real challenge is a massive skills gap, where entry-level roles are automated away, while new high-skill roles are created that the displaced workers are not equipped to fill.
This hurts new graduates and young professionals the most, removing the very rungs on the career ladder they need to climb. The future of work won’t be about finding a job that’s “AI-proof,” but about continuously learning the AI skills needed to stay relevant, productive, and valuable in an increasingly automated world. The disruption is no longer a future prediction; it’s already here.
AI How-To's & Tricks
Wordwall AI Trick: Secret Method to Unlock All Activities!

Wordwall is a powerhouse tool for educators, beloved for its ability to quickly create engaging quizzes, games, and printables for the classroom. With its new AI content generator, it’s become even more powerful. However, you might have noticed that the AI feature isn’t available on every activity template. But what if we told you there’s a simple yet brilliant Wordwall AI trick that lets you bypass this limitation and use AI-generated content for almost any activity type? In this guide, we’ll walk you through the secret method to supercharge your resource creation.

The Challenge: Limited AI Access in Wordwall
When you go to “Create Activity” in Wordwall, you’ll see a fantastic array of templates like Match up, Quiz, Crossword, and Unjumble. The new AI feature, marked by a “Generate content using AI” button, is a game-changer. Unfortunately, it’s currently only enabled for a select few templates, such as “Match up.” If you select a template like “Crossword” or “Type the answer,” you’ll find the AI option is missing.
This can feel limiting, but don’t worry. The solution doesn’t require complex workarounds; it just requires knowing how to leverage Wordwall’s own features in a clever way.
The Ultimate Wordwall AI Trick: A Step-by-Step Guide
The core of this method is to generate your content in an AI-enabled template first and then transfer it to the template you actually want to use. It’s a simple, three-step process.
Step 1: Generate Your Content with an AI-Enabled Template
First, start by creating an activity using a template that does have the AI function, like Match up. This will be your starting point for generating the core content.
- Log in to Wordwall and click Create Activity.
- Select the Match up template.
- Click the ✨ Generate content using AI button.
- In the pop-up window, describe the content you want. Be as specific as you like regarding the topic, language level, and number of items. For example, the video creator used this effective prompt to create a vocabulary exercise:
Can you generate a list of adjectives in English with the opposites. I want something at level B2 in English so upper-intermediate type vocabulary.
- Click Generate. The AI will quickly populate the keywords and definitions for your Match up activity.

Step 2: Switch the Template to Your Desired Activity
Now that your content is generated, you don’t have to stick with the “Match up” game. On the right-hand side of the screen, you’ll see the Switch template panel. This is the key to the entire Wordwall AI trick.
- Once your activity is created, look at the Switch template panel on the right.
- Click on Show all to see every available activity type.
- Now, simply select the template you originally wanted to use, such as Crossword.
Wordwall will instantly take your AI-generated list of words and their opposites and reformat them into a fully functional crossword puzzle, complete with clues! You’ve successfully applied AI-generated content to a template that doesn’t natively support it.
Step 3: Duplicate and Save Your New Activity (The Pro Move)
You’ve switched the template, but to keep both the original “Match up” and the new “Crossword” as separate activities, you need to perform one final, crucial step.
- Below your new crossword activity, click on Edit Content.
- A dialog box will appear. Instead of editing the original, choose the option: Duplicate Then Edit As Crossword.
- This will create a brand new, independent copy of the activity. You can now rename the title (e.g., from “Adjectives and Their Opposites” to “Crossword – Adjectives and Their Opposites”).
- Click Done to save.
When you check your “My Activities” folder, you’ll now have two separate resources: the original Match up game and the new Crossword puzzle, both created from a single AI prompt. You can repeat this process for quizzes, word searches, anagrams, and more!
Enhancing Your AI-Generated Activities
Once your content is in place, don’t forget about Wordwall’s other great features to make your activities even better:
- Add Audio: In the content editor, you can click the speaker icon next to a word to generate text-to-speech audio. This is fantastic for pronunciation practice in language learning.
- Set Assignments: Use the “Set Assignment” button to easily share the activity with your students. You can get a direct link or a QR code, making it perfect for both in-person and online classrooms.
Conclusion: Supercharge Your Teaching with Wordwall AI
The Wordwall AI trick is a powerful way to maximize efficiency and create a wide variety of high-quality teaching resources in a fraction of the time. By starting with an AI-enabled template, generating your core content, and then using the “Switch template” and “Duplicate” features, you can unlock the full potential of AI across the entire Wordwall platform. Give it a try and see how much time you can save on lesson preparation!
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