GenAI holds a lot of promise - but what are today’s practical use cases for data engineering? In this virtual event, discover how AI-driven #dataintelligence is helping data engineers build faster, more reliable pipelines. You’ll hear from experts on how the Databricks Data Intelligence Platform is revolutionizing data engineering by leveraging conversational AI, unifying workflows, simplifying pipeline operations, and more. https://dbricks.co/3MVGXF4
Javid Ur Rahaman
1mo
This is a fantastic initiative! Beyond building faster and more reliable pipelines, AI-driven data intelligence also enhances data quality and governance, ensures compliance, and enables real-time analytics. Integrating AI in data engineering is not just about efficiency; it's about transforming raw data into actionable insights with unprecedented accuracy. I look forward to hearing more about how Databricks is pushing the boundaries in this space! Rapidflow Inc Databricks
Todd Hower
1mo
Exciting
Head - Data Engineering, Quality, Operations, and Knowledge
1moAsk yourself how many trillions it would need to put a man via genAI to moon when all it took was a HP calculator that today may cost around 500 dollars. Gen AI does not hold any promise- its basic and foundational mathematics has hallucinations embedded into its stupidity. Making a thing that walks like a duck and talks like duck be a lion using rocket science and computation that puts the HP calculator which put man to moon to shame is not a promise 🤣