🔄 ETL Concepts

Extract Transform Load, Data Integration, Data Processing, Workflows

Amazon DocumentDB New Query Planner
docs.aws.amazon.com·15h·
Discuss: DEV
⚙data engineering
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Leverage data to contextualize competitive construction
constructiondive.com·4d
⚙data engineering
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RWA Specialist Centrifuge Debuts Tokenization Service, Starting with Daylight
finance.yahoo.com·1d
⚙data engineering
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Fluidware – an essay on software in the age of generative abundance
createdbyhonesty.com·21h·
Discuss: Hacker News, r/SoftwareEngineering
⚙data engineering
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Do you agree with Hinton's AI risk outlook?
livnlearns.com·1d·
Discuss: Hacker News
🤖ai
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GDX and SIL Offer Materials Exposure, But Differ In Fees, Yields, and Performance
fool.com·3h
⚙data engineering
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Coinbase Ventures-Backed Supra Offers $1M Bounty to Beat Its Parallel EVM Execution Engine
techstartups.com·23h
⚙data engineering
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From Charts to Code: A Hierarchical Benchmark for Multimodal Models
paperium.net·1d·
Discuss: DEV
⚙data engineering
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Webinar Analytics Guide: Measure Success & Boost Performance
dev.to·9h·
Discuss: DEV
⚙data engineering
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Sonova Holding AG (SONVY) Q2 2026 Earnings Call Transcript
seekingalpha.com·9h
⚙data engineering
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FastAPI + LangChain Customer Support Workflow (Micro Case Study)
dev.to·1d·
Discuss: DEV
⚙data engineering
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PepTriX: A Framework for Explainable Peptide Analysis through Protein Language Models
arxiv.org·1d
🤖ai
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The dawn of the AI-native database
infoworld.com·4d
🤖ai
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An Introduction to LangChain
dev.to·9h·
Discuss: DEV
🤖ai
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The Architecture of Traffic Arbitrage: A Professional's Blueprint
dev.to·2d·
Discuss: DEV
⚙data engineering
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This Little-Known AI Stock Is Up 311% in 2025, and History Says It Could Soar Again in 2026 (Hint: Not Palantir)
fool.com·1d
⚙data engineering
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Speculative Decoding: Making LLMs Faster Without Sacrificing Quality
dev.to·6h·
Discuss: DEV
🤖ai
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Reverse Engineering the M1C1 LiDAR: cracking the protocol without documentation
dev.to·2d·
Discuss: DEV
⚙data engineering
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Mastering SQL — From Zero to Hero
dev.to·3d·
Discuss: DEV
⚙data engineering
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PANDA - Patch And Distribution-Aware Augmentation for Long-Tailed Exemplar-Free Continual Learning
arxiv.org·1d
⚙data engineering
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