Colleen Tartow, Ph.D.

Colleen Tartow, Ph.D.

Field CTO and Head of Strategy at VAST Data

    Colleen Tartow, Ph.D. is Field CTO and Head of Strategy at VAST Data and has 20+ years of experience in data, analytics, engineering, and consulting. Adept at assisting organizations in deriving value from a data-driven culture, she has successfully led diverse data, engineering, and analytics teams through the development of complex global data management solutions and architecting enterprise data systems. Her demonstrated excellence in data, engineering, analytics, and diversity leadership makes her a trusted senior advisor among executives. An experienced speaker, author, valued mentor, and startup advisor, Colleen holds degrees in astrophysics and lives in Massachusetts.

    All Sessions by Colleen Tartow, Ph.D.

    Day 2 04/24/2024
    2:00 pm - 2:30 pm

    Data Mesh: where are we now?

    <span class="etn-schedule-location"> <span class="firstfocus">Data Engineering</span> </span>

    Data Mesh, the idea of a decentralized, domain-driven data architecture that puts data products at the forefront of an organization’s data strategy, took the data world by storm when it was introduced a few years ago. The idea of a prescriptive-yet-flexible methodology and people-first approach to data infrastructure design holds promise as businesses look to adopt a technology stack that will help them govern and serve data to consumers, with the ultimate goal of monetizing proprietary data. This talk will delve into the current state of Data Mesh adoption and implementation across various industries. It will explore the evolution of the Data Mesh concept since its inception, examining both its successes and challenges. Drawing from real-world case studies and industry trends, we will assess the practical implications of adopting a Data Mesh architecture, including its impact on organizational structure, technology stack, and data governance. Furthermore, the talk will address key questions and considerations for organizations looking to embark on their Data Mesh journey. Topics to be discussed include identifying suitable use cases for Data Mesh, overcoming cultural barriers to adoption, selecting appropriate tools and technologies, and ensuring data quality and security within a decentralized data ecosystem. With the recent addition of AI - specifically Deep Learning and Large Language Models (LLMs) - clear data strategies like Data Mesh become even more pertinent, as organizations seek scalable and efficient ways to leverage the truly vast amounts of data required for training and deploying such models. The emergence of LLMs emphasizes the importance of treating data as a product, as data products evolve into the foundational elements for training and refining these advanced algorithms. Additionally, in the context of stringent regulations and increasing demands for auditability, a cohesive data strategy is paramount. Organizations must ensure that data is not only accessible and actionable but also protected and compliant with regulatory requirements, by being subject to rigorous governance and auditing processes.

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