Cloud-native Semantic Layer on Data Lake

Download Slides

With larger volume and more real-time data stored in data lake, it becomes more complex to manage these data and serve analytics and applications. With different service interfaces, data caliber, performance bias on different scenarios, the business users begin to suffer low confidence on quality and efficiency to get insight from data.

Based on Apache Kylin, Apache Spark and other technology, Dong Li will introduce a cloud-native architecture, building unified semantic layer over data lake, to simplify data management and analytics over data lake. With data virtualization, single data-as-a-service API is provided to unify different sources and connect data silos. With unified semantic layer, data relations, lifecycle and logics are centrally managed to provide single source of truth for multiple applications. With cloud-native infrastructure, resources are allocated elastically to save TCO, and performance is boosted with enhanced distributed cache above separated computation and storage.

In this topic, Dong Li will outline the architecture and deep dive the techniques, and also real cases in top global bank in Europe who switched from traditional data warehouse options.

Speaker: Dong Li

Watch more Data + AI sessions here
Try Databricks for free
« back
About Dong Li


Founding Member & Head of Product in Kyligence, leading product lines and cloud business growth of Kyligence. He is also an Apache Kylin Committer and PMC member, focus on technical innovation and ecosystem expansion. Before joining Kyligence, he was a Senior Software Engineer in eBay and a Software Development Engineer in Microsoft.