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Mehul Thakkar

Power Query vs DAX: How to place logic correctly in Power BI

Power Query vs DAX: How to place logic correctly in Power BI

Leave a Comment / Power BI /

Many Power BI issues do not start with poor visuals or weak calculations. They start much earlier, when logic is placed in the wrong layer. Reports become slow, models turn confusing, and small changes take longer than they should. The question of whether logic should live in Power Query or DAX is not technical trivia. It directly affects performance, clarity, and long-term usability.

This blog explains how to think about that decision in a practical way.

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ChatGPT 5.2 is the most practical AI release of the year

ChatGPT 5.2 is the most practical AI release of the year

Leave a Comment / Artificial Intelligence /

AI model launches no longer create excitement the way they once did. Updates are frequent, version numbers keep changing, and many releases feel incremental. ChatGPT 5.2 arrived quietly, and most people barely noticed. Yet this version introduces changes that matter more in real work than in demos.

This blog explains what actually changed in ChatGPT 5.2, where it performs better, and why this update is more relevant than it initially appears.

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Kimi K2 versus GPT and Claude (Honest review of China’s latest AI tool)

Kimi K2 versus GPT and Claude (Honest review of China’s latest AI tool)

Leave a Comment / Artificial Intelligence /

Moonshot, a fast growing Chinese AI startup, recently introduced Kimi K2. It has created interest because of its long context window, natural reasoning style, and claims of competing with models like GPT 5 and Claude.

This blog gives a simple and honest review of what Kimi K2 does well, where it struggles, and what it means for users who rely on AI for real work.

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The truth about AI automation nobody tells you

The truth about AI automation nobody tells you

Leave a Comment / Artificial Intelligence /

Every week, there’s a new promise that AI will handle entire workflows from automating emails to managing complete projects. The hype sounds great, but a new benchmark from Scale AI and the Center for AI Safety shows a different reality.

In the study, AI agents were tested on real freelance tasks like writing, research, data entry, and design. Out of nearly $144,000 worth of work, the top model earned only about $1,800 completing just 2 to 3 percent of jobs successfully.

This doesn’t mean AI is weak. It means organizations are skipping the most important part of AI success: workflow design.

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