Non-Brand Data

“Non-Brand Data” delves into the realm of enterprise data management and AI applications, focusing on the challenges and solutions related to leveraging data beyond traditional branding contexts. The document explores topics such as the importance of understanding and utilizing diverse data sources, the pitfalls of treating data as static, and the necessity for AI systems to comprehend and interact with dynamic, living data. It also discusses the significance of secure knowledge base infrastructure, multi-tenancy architectures, and the role of technologies like Generative AI, Vector Embeddings, and Semantic Search in enhancing data understanding and retrieval processes.

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Why Valid SQL Returns Wrong Numbers

 Non-Brand Data

Three ways a query runs without an error and still returns the wrong number, with the query and the fix for each.

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My book is out: Python Data Analysis, Fourth Edition

 Non-Brand Data

Co-written with my co-author, and what the year of writing it was like.

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Fix it or throw it away: deciding what to do with an AI output

 Non-Brand Data

The harder part is knowing which problems you can fix and which ones mean starting over.

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Why Most GenAI Workflows Need a Review Loop

 Non-Brand Data

A Better Prompt Is Not Enough

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Manager Memo: Reviewing GenAI Output Before It Reaches Stakeholders

 Non-Brand Data

A guide for managers who approve AI-assisted work: what to check, when to reject, and how to talk to stakeholders about it.

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What Most GenAI Evaluation Workflows Get Wrong

 Non-Brand Data

Reliability is not a property of the final answer. It is a property of the whole system that produced it.

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From Prompt to Reliable Output: A Practical GenAI Evaluation Workflow

 Non-Brand Data

A concise guide to achieve success in your production GenAI generation

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Best MCP Servers for Stock Market Data

 Non-Brand Data

The best MCP servers for connecting AI agents to financial workflow

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The GenAI Skill Data Professionals Need Most: Evaluation

 Non-Brand Data

Only by evaluating things that we know our system is good.

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The ML Skills That Still Matter in 2026

 Non-Brand Data

The skills that still make you desirable by companies and ahead of everyone

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What Real SQL Work Taught Me About Being a Data Scientist

 Non-Brand Data

Why I stopped seeing SQL as a secondary skill and started seeing it as the backbone of real data projects

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Best Stock Market data API in the AI Agent era

 Non-Brand Data

How modern financial APIs are powering the next generation of AI-driven market research and trading tools

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