Data architecture is the foundation of every organization’s data strategy, but it's not just something for CIOs and data architects either — everyone at data-powered organizations can benefit from understanding the ways data moves between teams and flows into data projects to yield insights.
Grant is a Customer-Facing Data Scientist and Analytics Architect with Dataiku. In this and his prior roles, Grant has spent time with 100+ companies understanding and architecting solutions for both business analytics and data science platforms. When not working with Dataiku clients, Grant is a Lecturer at Columbia University in the Applied Analytics program and enjoys volunteering at his son's school.
Harizo has a background in mathematics and computer science and holds a PhD in Computational and Applied Mathematics from the University of Lille. He works on the R&D team at Dataiku, focusing on technical ecosystem integrations, particularly the challenges of enterprise-grade deployments (security, availability, and scalability).
Key data architecture terms explained from a non-technical perspective
Illustrated examples of data architecture concepts
Why data architecture matters for non-data architects