{"id":1240,"date":"2025-10-09T16:40:32","date_gmt":"2025-10-09T16:40:32","guid":{"rendered":"https:\/\/datadecoded.com\/mcr\/?post_type=seminar&#038;p=1240"},"modified":"2025-10-09T19:45:16","modified_gmt":"2025-10-09T19:45:16","slug":"panel-rethinking-the-data-stack-when-ai-understands-the-mess-we-tried-to-clean","status":"publish","type":"seminar","link":"https:\/\/datadecoded.com\/mcr\/seminars\/panel-rethinking-the-data-stack-when-ai-understands-the-mess-we-tried-to-clean\/","title":{"rendered":"PANEL: Rethinking the Data Stack: When AI Understands the Mess We Tried to Clean"},"content":{"rendered":"<p>Data architecture has always been about control \u2014 making messy data usable through standardisation and transformation. But AI models now thrive on the very messiness we\u2019ve spent years taming. In this provocative discussion, leaders from Lloyds Banking Group, Mars, and Google debate whether our obsession with structure is holding us back. Is it time to replace rigid ETL workflows with adaptive, AI-native data platforms that learn context rather than enforce it?<\/p>\n<div class=\"elementToProof\"><b>Takeaways:<\/b><\/div>\n<ul data-start=\"378\" data-end=\"1406\">\n<li>\n<div class=\"elementToProof\" role=\"presentation\"><b>AI shifts the value from structure to context.<\/b><br \/>\nTraditional ETL and modelling\u00a0pipelines were built to <i>impose order<\/i>\u00a0on data; AI can now <i>interpret meaning<\/i>\u00a0from disorder. The future of data engineering is less about cleaning and more about capturing rich, contextual signals.<\/div>\n<\/li>\n<li>\n<div role=\"presentation\"><b>The modern data platform isn\u2019t dead \u2014 it\u2019s evolving.<\/b><br \/>\nInstead of dismantling what we\u2019ve built, AI invites a rethink of architecture: blending structured and unstructured layers, integrating vector stores, and enabling semantic search and retrieval-augmented pipelines.<\/div>\n<\/li>\n<li>\n<div role=\"presentation\"><b>Governance, trust, and lineage still matter \u2014 maybe more than ever.<\/b><br \/>\nAs AI consumes raw data, we need new ways to measure quality, provenance, and bias. \u201cUnstructured\u201d doesn\u2019t mean \u201cungoverned.\u201d<\/div>\n<\/li>\n<li>\n<div role=\"presentation\"><b>Data teams must evolve from pipeline builders to data product designers.<\/b><br \/>\nThe role of data architecture expands beyond moving data \u2014 to <i>designing experiences<\/i>\u00a0that make it discoverable, interpretable, and safe for AI-driven systems.<\/div>\n<\/li>\n<\/ul>\n","protected":false},"template":"","class_list":["post-1240","seminar","type-seminar","status-publish","hentry"],"acf":{"start_time":"2025-10-22 16:10:00","end_time":"2025-10-22 16:40:00","theatre":636,"speakers":[1003,1132,619,1245],"businesses":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.6 (Yoast SEO v26.6) - 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