Google Cloud NEXT '26の後、AI駆動のデータアナリストのように考えてみた — 変わったこととは

🚀 Introduction After exploring the announcements from Google Cloud NEXT '26, I realized something important: The role of a data analyst is changing — not in the future, but right now. Tasks that once required hours of SQL writing, data cleaning, and dashboard building are now being assisted by AI-powered tools. So instead of just reading updates, I asked myself: 👉 If I start learning data analytics today, what should I do differently? This article is my perspective. 🔍 The Shift: From Query Writing → Problem Solving Traditionally, data analysis followed this process: Writing SQL queries Cleaning datasets Aggregating results Creating dashboards But the tools highlighted at Google Cloud NEXT '26 suggest a new workflow: Define the business problem Use AI to assist with queries Focus on interpreting results Drive decisions 👉 The value is shifting from writing queries to thinking clearly. 🧪 A Simple Example A basic SQL query: SELECT region, SUM(sales) FROM sales_data GROUP BY region; Previously, you needed: Strong SQL knowledge Manual debugging Now, AI tools can: Generate the query Optimize it Explain the output This lowers the barrier for beginners and speeds up learning. ⚖️ What I Liked Faster analysis Easier learning curve Reduced repetitive work ⚠️ What Concerns Me Over-reliance on AI Weak understanding of fundamentals Risk of treating results as a “black box” 💡 My Take AI will not replace data analysts. It will upgrade them. Future analysts need: Strong SQL and statistics Ability to validate AI outputs Business thinking 👉 AI is a tool, not a replacement. 🧠 My Updated Learning Plan After exploring NEXT '26, I’m focusing on: Learning SQL deeply Understanding cloud tools Using AI as a support system, not a shortcut 💬 Your Thoughts? Do you think AI will simplify data analysis or make it more complex? Google Cloud NEXT '26 didn’t just introduce tools — it showed how the role itself is evolving. 👉 Don’t just learn tools. Learn how the role is changing. 💬 Your Thoughts? Do you think AI will simplify data analysis or make it more complex? 🚀 Introduction After exploring the announcements from Google Cloud NEXT '26, I realized something important: The role of a data analyst is changing — not in the future, but right now. Tasks that once required hours of SQL writing, data cleaning, and dashboard building are now being assisted by AI-powered tools. So instead of just reading updates, I asked myself: 👉 If I start learning data analytics today, what should I do differently? This article is my perspective. 🔍 The Shift: From Query Writing → Problem Solving Traditionally, data analysis followed this process: Writing SQL queries Cleaning datasets Aggregating results Creating dashboards But the tools highlighted at Google Cloud NEXT '26 suggest a new workflow: Define the business problem Use AI to assist with queries Focus on interpreting results Drive decisions 👉 The value is shifting from writing queries to thinking clearly. 🧪 A Simple Example A basic SQL query: SELECT region, SUM(sales) FROM sales_data GROUP BY region; Previously, you needed: Strong SQL knowledge Manual debugging Now, AI tools can: Generate the query Optimize it Explain the output This lowers the barrier for beginners and speeds up learning. ⚖️ What I Liked Faster analysis Easier learning curve Reduced repetitive work ⚠️ What Concerns Me Over-reliance on AI Weak understanding of fundamentals Risk of treating results as a “black box” 💡 My Take AI will not replace data analysts. It will upgrade them. Future analysts need: Strong SQL and statistics Ability to validate AI outputs Business thinking 👉 AI is a tool, not a replacement. 🧠 My Updated Learning Plan After exploring NEXT '26, I’m focusing on: Learning SQL deeply Understanding cloud tools Using AI as a support system, not a shortcut 💬 Your Thoughts? Do you think AI will simplify data analysis or make it more complex? Google Cloud NEXT '26 didn’t just introduce tools — it showed how the role itself is evolving. 👉 Don’t just learn tools. Learn how the role is changing. 💬 Your Thoughts? Do you think AI will simplify data analysis or make it more complex?