Kevin Petrie

Kevin Petrie

North Yarmouth, Maine, United States
25K followers 500+ connections

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About

Teach early adopters about emerging AI, data, and analytics technologies. As a thought…

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Activity

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Experience

  • BARC Graphic

    BARC

  • -

    Greater Boston Area

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    Newton, MA

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    Greater Boston Area

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    Burlington, MA

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    Greater Boston Area

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    Hopkinton, MA

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    Hopkinton, MA

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    Hopkinton, MA

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    Cupertino, CA

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    Cupertino, CA

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    New York City and San Francisco

Education

Licenses & Certifications

Volunteer Experience

  • Chair, Finance Committee

    Bustins Island Villagers Corp.

    - 1 year 8 months

  • Coach of boys lacrosse team

    Cumberland North Yarmouth Youth Lacrosse

    - Present 1 year 7 months

    Children

Publications

  • Conversing with Data: The Impact of Generative AI on Business Intelligence

    Eckerson Group

    Conversational business intelligence (BI) marks the latest effort to break the analytics bottleneck and help companies make more data-driven decisions. This emerging technology uses generative artificial intelligence (GenAI) to guide and automate the various tasks of business intelligence through a chatbot.

    Other authors
    See publication

  • Governed Data Management for Generative AI: Challenges, Requirements, and Use Cases

    Eckerson Group

    To realize the potential benefits of generative AI, companies must strengthen five processes: data integration (including provisioning), cataloging, master data management, data observability (encompassing data quality and pipeline performance), and governance. Only after they strengthen these processes for multi-structured data, including traditional tables and unstructured text, can they generate trustworthy outputs that drive smart action.

    See publication

  • Governing Cost with FinOps for Cloud Analytics: Program Elements, Use Cases, and Principles

    Eckerson Group

    Implemented well, a FinOps program can drive measurable, achievable returns on investment (ROI) for cloud-based analytics projects.

    See publication

  • Modern Data Pipelines: Trends and Tools You Should Know

    Eckerson Group

    As enterprises democratize data consumption and invest in advanced analytics, they need ever-higher volumes of complex, fast-moving data. To meet this demand, data teams need to accelerate the development of data pipelines, automate their execution, and continuously validate the quality of the output. Along the way, they need to master the lifecycle of data, from ingestion and transformation to testing, orchestration, and monitoring.

    See publication

  • Data Observability: Practices, Products, and Frameworks You Need to Know

    Eckerson Group

    The evolving discipline of data observability seeks to ensure both data quality and data pipeline performance, using techniques adapted from governance tools and application performance management. It monitors indicators, correlates them, identifies issues, assesses root causes, generates alerts, and remediates issues.

    See publication

  • Deep Dive on Machine Learning Platforms: Three Tools to Consider

    Eckerson Group

    Enterprises need to foster open collaboration between business owners, data scientists, machine learning (ML) engineers, and data engineers. The machine learning platform enables these cross-functional teams to build and manage ML projects as part of an efficient, governed, and scalable process. This deep dive profiles three leading products with three different approaches and concludes with questions to help evaluate any ML platform to find the right product for your needs.

    See publication

  • Autonomous Data Management: Requirements, Use Cases and Guidelines

    Eckerson Group | Sponsored by Informatica

    Data teams need to get more productive, and fast, to reconcile booming data supply and demand.
    Autonomous data management (AutoDM) solutions can help ease bottlenecks for data teams by using
    metadata, automation, and artificial intelligence to standardize and accelerate data delivery. While the
    concept is not new, advances in computing power and advanced analytics algorithms make AutoDM viable for many modern enterprises.

    See publication

  • Log Analytics for CloudOps: Making Cloud Operations Stable and Agile

    Eckerson Group report

    The cross-functional discipline of Cloud Operations (CloudOps) applies ITOps and DevOps methodologies to the management of cloud applications and infrastructure. This requires effective analytics of logs—those tiny files that capture events such as user actions, application tasks, and compute errors, as well as the messages that applications and cloud components send to one another.

    See publication

  • The Rise of Streaming ETL: Transforming Data in Flight for Real-Time Insight and Action

    Eckerson Group

    The confluence of digital transformation, data democratization, and data modernization create the opportunity for real-time data integration, which in turn drives real-time business insights and action. Streaming extract, transform, and load (ETL) has emerged as the most efficient, effective method of real-time data integration.

    See publication

Projects

  • CDOIQ Editorial Board

    The Chief Data Officer and Information Quality (CDOIQ) Symposium is one of the key events for sharing and exchanging cutting-edge ideas, content and discussions. Our purpose is to advance the knowledge and accelerate the adoption of the Chief Data Officer (CDO) role in all industries and geographical countries. As Data is a critical aspect of every organization, the symposium is focusing on the management and leadership of this critical element for the 21st century that will benefit every…

    The Chief Data Officer and Information Quality (CDOIQ) Symposium is one of the key events for sharing and exchanging cutting-edge ideas, content and discussions. Our purpose is to advance the knowledge and accelerate the adoption of the Chief Data Officer (CDO) role in all industries and geographical countries. As Data is a critical aspect of every organization, the symposium is focusing on the management and leadership of this critical element for the 21st century that will benefit every organization.

    Against the backdrop of Data Analytics, Machine Learning, Data Quality, and Data Management, the CDOIQ Symposium will host its event physically on-site at Hyatt Regency Cambridge Hotel and live-streamed virtually through the Whova platform and will explore delivering mature data & analytics capabilities for ROI, including local organizational issues to global challenges, through case studies from industry, academic, financial, government and healthcare leaders.

    See project

  • Chair, Panel Debate: Data Mesh - What You Need to Know

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    Data Mesh has been one of the most talked about trends in Data in the last year. In this panel Starburst CEO, Justin Borgman, Founder of the Data Mesh concept, Zhamak Dehghani, Omar Khawaja, Head of Analytics at Pharmaceutical giant Roche, Cindi Howson, Chief Data Strategy Officer at Thoughtspot and Kevin Petrie of Analyst firm Eckerson Group tackle why Data Mesh has gone mainstream, exactly what you need to know before starting a project and the potential benefits associated with adoption.

    See project

  • CDO TechVent on Data Observability

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    CDO TechVent is an innovative, half-day, virtual event for data and analytics leaders that provides practical advice for selecting and implementing emerging technologies.

    Data observability is an emerging discipline for studying the health of enterprise data environments, using techniques adapted from governance tools and application performance management. It includes data quality observability, which monitors the quality and timeliness of data. It also includes data pipeline…

    CDO TechVent is an innovative, half-day, virtual event for data and analytics leaders that provides practical advice for selecting and implementing emerging technologies.

    Data observability is an emerging discipline for studying the health of enterprise data environments, using techniques adapted from governance tools and application performance management. It includes data quality observability, which monitors the quality and timeliness of data. It also includes data pipeline observability, which monitors the quality and performance of data pipelines, including the infrastructure that supports them.

    See project

Languages

  • English

    Native or bilingual proficiency

  • Spanish

    Professional working proficiency

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