This session looks at the emergence of AI and graph analytics in data management and how it is helping to automate, assist and accelerate the preparation and production of trusted data assets in a data driven enterprise. It looks at the use of AI in databases, data catalogs, data governance, ETL and self-service data preparation and in BI tools and Data Science. It also looks at the emergence of metadata knowledge graphs and how graph analytics can help to identify compliance issues, and recommend new data to improve predictions and insights
Target Audience: Data Engineer, CDO, Data Architect, Project Leader, Enterprise Architect, Head of BI/Analytics
Prerequisites: Basic knowledge of data management and BI
Level: Professional
Extended Abstract
This session looks at the emergence of AI and graph analytics in data management and how it is helping to automate, assist and accelerate the preparation and production of trusted data assets in a data driven enterprise. It looks at the use of AI in databases, data catalogs, data governance, ETL and self-service data preparation and in BI tools and Data Science. It also looks at the emergence of metadata knowledge graphs and how graph analytics can help to identify compliance issues, and recommend new data to improve predictions and insights