You've learned about AI models and applications. But how do the big names like ChatGPT, Gemini, and Claude actually work with data and analytics?

Each major AI tool runs on specific "engine" models, and understanding this ecosystem helps you choose the right tool for your data workflows.

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Which AI tool have you used for data analysis or visualization?

ChatGPT, made by OpenAI, excels at data analysis and code generation. But here's the key - it's powered by different versions of GPT models!

GPT-3.5, GPT-4, and newer versions like GPT-4o are the actual "brains" inside. ChatGPT is just the interface that helps you write Python, SQL, or interpret datasets.

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Have you tried asking ChatGPT to explain a complex data pattern?

Google's Gemini (formerly Bard) works the same way but shines in data visualization. It's powered by Google's own model family - also called Gemini!

They have Nano (for mobile analytics), Pro (balanced data processing), Ultra (complex statistical analysis), and Flash (quick data queries). Each serves different data needs.

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Have you noticed Gemini integrated into Google Sheets or BigQuery?

Claude, created by Anthropic, follows a poetic naming pattern. Its models are Haiku (quick data summaries), Sonnet (balanced analysis), and Opus (deep statistical modeling).

Claude excels at analyzing long reports and datasets - up to 200,000 words of data documentation!

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Would you use AI for quick data summaries or comprehensive analytics reports?

Here's something powerful for data teams - these companies can upgrade the "engine" without changing your workflow!

ChatGPT might upgrade from GPT-4 to GPT-4.5, improving data analysis accuracy while keeping the same interface. Better models mean better insights from your data.