Session: Data Mesh and the Modern Data Stack
Since the onset of modern computing, practices around data management for business analytics have largely been dictated by hardware constraints. As these constraints are lifted through the introduction of cloud computing and managed services, managing data infrastructure has become far less challenging, while performance and scalability have increased manifold across technology stacks. However, the so-called “modern data stack” is still predicated on the same legacy paradigm, simply with modern infrastructure. The concept remains unchanged: move data away from the source in order to do analytics and gain business value. Moreover, the organizational paradigms around data and analytics have largely remained the same despite robust evidence of inefficiencies. So the question remains: what should a truly modern data stack look like? How can an organization align itself with getting value out of data reliably and efficiently?
From data engineering to business analytics, the technical and organizational structure around data must be aligned with the idea of data as a first-class business product - only then can analytics reach its potential in strategic value terms. In this talk I will explore the traits of a truly modern data and analytics organization. I’ll discuss how to optimize around extracting strategic value from data, including why Data Mesh is the next logical step in that journey.
- What we think of as the "modern data stack" is based in legacy technologies, and we should think outside that box to truly evolve our data ecosystems.
- A truly modern data stack will take advantage of the latest advances in hardware and managed services to reduce time to value of data.
- Decentralized data architectures like Data Mesh are the next evolutionary step in modern data management.
Colleen Tartow, Ph.D. has over 20 years of experience in data, advanced analytics, engineering, consulting, and she has been obsessed with data her entire life. Adept at assisting organizations in deriving value from a data-driven culture, she has successfully led large data, engineering, and analytics teams through the development of complex global data management solutions, and architecting front- and back-end SaaS and enterprise data systems. Colleen is also experienced in building and leading diverse teams through business reorganization and transforming existing data ecosystems, maturing them into modern and robust technology stacks. She is determined to make engineering organizations better for both humans and business through mentoring, leadership, and streamlining processes. Her demonstrated excellence in data and engineering leadership makes her a trusted senior advisor among executives, and her work has led to her speaking at a variety of events in the technology leadership space, and mentoring aspiring leaders in data, analytics, and technology. Colleen is the co-founder of The Sequel, a newsletter exploring the human side of data. She is currently director of engineering at Starburst, holds a Ph.D. in astrophysics, and lives in Massachusetts.