AI-Augmented Data Management and Analytics
Wednesday, October 21, 2020
08:00 AM - 08:50 AM
Intermediate
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.
You will learn:
- What do we mean by AI in Data Management?
- Ways in which AI can assist in data and analytics
- AI in the database
- AI in data catalogs
- AI in Data Governance
- Using AI in ETL and self-service data preparation to speed up development and improve performance
- Knowledge graphs — the new way to store metadata
- What can graph analytics on a metadata knowledge graph tell you?
- AI in BI tools and Data Science
Mike Ferguson is Managing Director of Intelligent Business Strategies Limited. As an independent IT industry analyst and consultant he specializes in business intelligence/analytics, data management, big data, and enterprise architecture. With over 39 years of IT experience, Mike has consulted for dozens of companies on BI/Analytics, data strategy, technology selection, enterprise architecture, and data management. Mike is also conference chairman of Big Data LDN, the fastest-growing data and analytics conference in Europe. He has spoken at events all over the world and written numerous articles. He was formerly a principal and co-founder of Codd and Date Europe Limited – the inventors of the Relational Model, and a Chief Architect at Teradata on the Teradata DBMS. He teaches master classes in: Data Warehouse Modernization, Big Data, Enterprise Data Governance, Master Data Management, Building, Managing, and Operating an Enterprise Data Lake, Machine Learning and Advanced Analytics, Fast Data and Real-time Analytics, Data Virtualization, and Migrating to a Cloud Data Warehouse.