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Andrzej Garyel
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Data Engineering
4
min read
Delta Live Tables (DLT) vs dbt: Where Transformation Ends, and Platform Engineering Begins
DLT or dbt? Learn how to navigate the trade-offs between managed execution and vendor portability with a maturity checklist designed for modern data teams.
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Data Engineering
5
min read
Batch vs Streaming vs Micro‑Batch in CPG and Retail: Stop Overpaying for ‘Real‑Time’ That Doesn’t Deliver ROI
Find out why faster isn’t always better, explore a pragmatic guide to matching data latency with your organization’s ability to act, ensuring your architecture delivers ROI, not just noise.
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Data Engineering
7
min read
AI‑Assisted Data Engineering: How to Use GenAI for Pipeline Incident Triage (Without Creating Chaos)
Learn how to use GenAI as your incident triage assistant, how to speed up pipeline debugging, build smarter runbooks, and cut MTTR without creating new operational risks.
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Data Engineering
6
min read
Beyond the Hype: Why Data Engineering Needs Proof-of-Value (PoV) Instead of Proof-of-Concept (PoC)
Learn why transitioning from a tech-centric Proof-of-Concept to a business-first Proof-of-Value is the critical step to escaping "innovation purgatory" and delivering measurable ROI in your Data Engineering AI initiatives.
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Data Engineering
5
min read
Smarter, schneller, stärker: Das KI‑gestützte Betriebsmodell für Data Engineering
ntdecken Sie ein leichtgewichtiges, KI-gestütztes Operating Model, das laute Pipeline-Ausfälle in schnelle, auditierbare Wiederherstellungen verwandelt, den Engineering-Aufwand messbar reduziert und Geschäftsentscheidungen schützt.
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