INSIGHTS

DRILL TO DETAIL PODCAST

Mark Rittman is joined each episode by a special guest from the world of business intelligence, analytics and big data.

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Drill to Detail Ep.81 'Meltano, Singer Taps and Open-Source Data Pipelines' with Special Guest Douwe Maan

Mark Rittman is joined in this episode by Gitlab.com Lead Developer Douwe Mann to discuss the history of the open-source Meltano project and its recent refocus on becoming the "glue" that creates open-source data pipelines, using plugin technologies such as Singer Taps and dbt transformations.

Mark Rittman is joined in this episode by GitLab.com Lead Developer Douwe Maan to discuss the history of the open-source Meltano project and its recent refocus on becoming the "glue" that creates open-source data pipelines, using plugin technologies such as Singer Taps and dbt transformations.

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Data Engineering Mark Rittman Data Engineering Mark Rittman

Drill to Detail Ep.63 'Stitch, Talend and the Evolution of Data Pipelines' with Special Guest Jake Stein

Mark Rittman is joined by returning Special Guest Jake Stein, former co-founder and CEO of Stitch and now SVP of Stitch at Talend to talk about the evolution of the data pipeline-as-a-service, data catalogs and data governance and the vision behind Talend’s acquisition of Stitch. 

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Vendor Strategy, Data Engineering Mark Rittman Vendor Strategy, Data Engineering Mark Rittman

Drill to Detail Ep.40 'Fivetran's Middleware for SaaS Data' With Special Guest Taylor Brown

Mark Rittman is joined in this episode by Taylor Brown from Fivetran to talk about middleware for SaaS data, their focus on integrations with SaaS vendors and how this differentiates their offering, his thoughts on packaged analytic applications announced at the recent Looker Join conference ... and where the name "Fivetran" came from.

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Drill to Detail Ep.9 'Streamsets, Data-in-Motion and Data Drift' with Special Guest Pat Patterson

Mark Rittman is joined by StreamSets' Pat Patterson, talking about data in motion and doing it at scale, the story behind StreamSets and the problem of data drift, and the challenges involved in managing dataflows at scale as a continuous operation.

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