The terms Data Mesh and Data Fabric have been used extensively, and sometimes interchangeably, as data management solutions for enterprises to manage and derive value from their data. When considering the advances in AI capabilities, it becomes crucial to organize and access data from all corners of an organization, and successful implementation of either a mesh or fabric depends as much on the technical environment as on the capacity of people to support it.

In this presentation, we will:

• Explain these architectures with examples.
• Explain the overlaps and the differences when adopting either approach.
• Dive into the top three non-technical factors that must be addressed for a sustainable solution that can meet the expectations of the organization.

By conducting an organizational review against the characteristics of these two models and the factors for successful implementation, a best-fit plan for implementation can be crafted.

Speaker: Andrea Heithoff

Principal Architect
MITRE

Andrea Heithoff is a MITRE Principal Architect for Data Management Innovation who has advised Federal CDOs, CIOs, and Chief Architects. Since the passage of the Evidence Act of 2018, she has assisted new CDOs implement plans that balance technology innovation with effective organizational design and stakeholder engagement so they are best equipped to lead their organization's use of data as a strategic asset. She currently works in MITRE Labs in support of the U.S. Army.

Speaker: Savithri Devaraj

Savithri Devaraj is a Lead Data Engineer in MITRE Labs, with extensive experience in data architectures and data engineering. She has worked with several agencies in setting up their data architectures and governance programs. Her expertise in AWS cloud architectures, data management, and interoperability has helped her identify challenges, knowledge gaps, and policy considerations in implementing programs of record. Her current focus is data governance in the U.S. Army as it becomes a data-centric organization.