Скачать или смотреть AI Readiness Pillar #1: Trust — Data Quality Introduction

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Start here — GitHub Starter Kit Walkthrough
   • AI-Ready Data: GitHub Starter Kit Walkthrough  

Pillar #1 — Trust (Data Quality)
Intro:    • AI Readiness Pillar #1: Trust — Data Quali...  

Code:    • AI Readiness Pillar #1 (Code): Data Qualit...  

Pillar #2 — Control (Governance & Security)
Intro:    • AI Readiness Pillar #2: Control — Governan...  

Code:    • AI Readiness Pillar #2 (Code): Governance ...  

Pillar #3 — Context (Semantics & Metadata)
   • AI Readiness Pillar #3: Context — Semantic...  

Pillar #4 — Feedback (Closed-Loop Learning)
   • AI Readiness Pillar #4: Feedback — Closed-...  

GitHub repo:
https://github.com/AhmedMahmoud2/data...

This video introduces AI Readiness Pillar #1: Trust — focusing on data quality and reliability.

Before AI models, prompts, or GenAI tools, organisations must be confident that their data is accurate, consistent, and reliable.

In this introduction, I explain:
• Why trust is the first pillar of AI readiness
• What data quality really means in practice
• How poor data undermines AI outcomes
• How data contracts and validation create reliability

In Part 2, these concepts are implemented in code using Great Expectations.

GitHub starter repo:
👉 https://github.com/AhmedMahmoud2/data...