Data environments are becoming increasingly complex to navigate, and this has proven to be a significant obstacle in enterprise self-service adoption and data science projects.
The solution is to incorporate six fundamental components that make up a data unification environment: data discovery and cataloging, data governance with security, self-service data, collaboration, cloud optimization, and AI assistance. These are the necessary components for empowering end users to work with, collaborate on, and publish data. Data preparation and data virtualization are two well-accepted techniques used to deliver a unified environment that masks complexity and enables people to efficiently find and work with data.
This session will lay the foundation for data unification and then explore both data virtualization and data prep best practices.
You Will Learn
- Six data unification components needed to effectively facilitate user self-sufficiency
- How data unification optimizes the modern analytics lifecycle user experience
- Understanding data virtualization and best practices to unify data
- Understanding data prep and best practices for self-service data analytics
- Analytics leaders, CDO/CAO/CIO, enterprise architects, data architects, database administrators, data modelers, integration architects, ETL/DW developers, business analysts