{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Data Science Tech Brief By HackerNoon","title":"How To Power AI, Analytics, and Microservices Using the Same Data","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/f551ef43\"></iframe>","width":"100%","height":180,"duration":531,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/how-to-power-ai-analytics-and-microservices-using-the-same-data.\n             Adam Bellemare explains how data streaming unifies AI, analytics, and microservices—solving data access challenges through real-time, scalable pipelines. \n            Check more stories related to data-science at: https://hackernoon.com/c/data-science.\n            You can also check exclusive content about #data-streaming-architecture, #confluent, #adam-bellemare, #event-driven-microservices, #generative-ai-data-pipelines, #apache-kafka, #real-time-analytics, #good-company,  and more.\n            \n            \n            This story was written by: @confluent. Learn more about this writer by checking @confluent's about page,\n            and for more stories, please visit hackernoon.com.\n            \n                \n                \n                Adam Bellemare, Principal Technologist at Confluent, explores how data streaming solves long-standing data access issues for AI, analytics, and microservices. By decoupling producers from consumers and enabling real-time, low-latency data flow, streaming creates a unified data layer that powers GenAI, RAG, and event-driven systems across organizations.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/8VxAgS1Ll3FJEERcAdhFdqqXJMnE7OfD2RUvrjauLt0/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjY4LzE2ODM1/ODI1ODUtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}