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Is Data Engineering Dead in 2026? 💀 Before you quit, read this. Let’s be real: If your job is just boilerplate SQL and moving data from A to B, AI is coming for you. 🤖 But for the rest of us? The game hasn't ended; it just got a...

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thekruk

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265,700 просмотров • 10 месяцев назад •via TikTok

Наука и технологии#tech#ai#coding#dataanalysis#dataengineer
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The internet is evolving - are you ready? 🌐⚡ At SUI DePIN, your data isn’t just collected - it’s owned by you. Monetize it. Secure it. Power the next generation of AI on the Sui! ✅ Own your data ✅ Earn real rewards ✅ Fuel AI innovation No middlemen. No limits. Just you and your data. Step into the future today 👉
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The internet is evolving - are you ready? 🌐⚡ At SUI DePIN, your data isn’t just collected - it’s owned by you. Monetize it. Secure it. Power the next generation of AI on the Sui! ✅ Own your data ✅ Earn real rewards ✅ Fuel AI innovation No middlemen. No limits. Just you and your data. Step into the future today 👉

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AI needs data to grow. But accessing high-quality datasets is becoming harder than ever. · Data collection is increasingly centralized in the hands of a few large players. · Platforms are locking content behind expensive APIs and private data deals. · Specialized datasets (medical, legal, code) can cost 20–40× more than general web data. · And while 94% of companies are exploring Gen-AI, only 12% have reliable data channels. The result? A growing data bottleneck for AI development. The future of AI won’t just depend on better models. It will depend on who can access and activate quality data.
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AI needs data to grow. But accessing high-quality datasets is becoming harder than ever. · Data collection is increasingly centralized in the hands of a few large players. · Platforms are locking content behind expensive APIs and private data deals. · Specialized datasets (medical, legal, code) can cost 20–40× more than general web data. · And while 94% of companies are exploring Gen-AI, only 12% have reliable data channels. The result? A growing data bottleneck for AI development. The future of AI won’t just depend on better models. It will depend on who can access and activate quality data.

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🚀 My New Book is Here: Data Strategy (3rd Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.
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AI runs on data. Your data. Tech giants scrape the internet, collect user interactions, and buy datasets to train their models. Now, platforms are charging companies to access the data you created. It doesn't have to be this way. Join the data revolution. Own your data, own your impact.

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OpenAI's Deep Research is getting a run for its money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!

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AI runs on data. but most of it is stale, outdated, static. what if intelligence was powered by living signals from real human activity? introducing: 𝐳𝐃𝐚𝐭𝐚 - the Data Layer Powering Zentry and The AI Data Economy ⇢

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Imagine this: Data is the lifeblood of AI. No matter how advanced, AI is only as good as the data it learns from. The catch? Most AI runs on outdated, biased, or limited data—like trying to win a marathon in flip-flops. 💡The problem isn’t AI itself—it’s how data is collected, processed & controlled by a few big players. OptimAI Network flips the script! 🔹No centralized silos 🔹No intrusive scraping 🔹A decentralized ecosystem where you power AI’s future Read more:

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What if the next big leap in AI comes from data that’s never been on the internet? Most AI models learn from publicly available information, but companies hold enormous amounts of valuable private data. DataVendor is changing that with a marketplace where companies can sell access to their data to AI labs, helping train smarter AI. With 4,000+ vendors and 50K+ assets already listed, this could be huge.

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The UK government was just defeated for the 3rd time by the House of Lords, who have demanded again that AI companies disclose their training data. The government seems desperate to appease big tech, but the Lords are consistently saying they must instead defend creators. This is the biggest defeat for the government yet. Baroness Kidron perfectly makes the case for why training data transparency is necessary: "Because what you can't see you can't enforce."

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At Open AGI, our CEO Ahmed Rashad shared why trust is the new compute. AI is moving from generating content to making life-or-death decisions — medical diagnoses, autonomous vehicles, military systems. If the training data is wrong, the decisions are wrong. Meanwhile, models are increasingly trained on synthetic outputs, creating feedback loops that degrade quality. Data supply chains are opaque. Adversarial attacks are real. The next AI race won’t be won by bigger models. It will be won by those who control and verify the data layer. Perle Labs is building the sovereign, human-verified, on-chain auditable infrastructure high-stakes AI requires. Trust wins the AI race. Thank you Sentient for having us! No better way to end off our time at ETHDenver 🏔🦬🦄. Until next time 🫡

Perle Labs

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Introducing Snowflake Workspaces — the unified environment where developers build, test, and collaborate on data and AI projects. Code in SQL, Python, or @Streamlit — all inside the Snowflake AI Data Cloud. Fast. Secure. Built for the way you work.

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