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#9 - Travis Dent - DevOps & Project Management
🎙️ Travis Dent: Data Engineer at Xebia
In this episode, Travis, an experienced professional in data engineering and DevOps, shares his journey from robotics to data analytics. The discussion covers the importance of DevOps practices in data projects, addressing challenges like long-running pipelines and changing data schemas. Travis emphasizes the cultural aspects of DevOps, including collaboration, automation, and continuous improvement, while also touching on different levels of DevOps knowledge for data professionals.
The conversation explores how project management and clear vision contribute to successful data initiatives. Travis and the host discuss how the data field can learn from other industries like aviation and construction, particularly reliability and alerting. The episode concludes with practical recommendations for listeners looking to enhance their DevOps skills, including book suggestions and online resources, making it valuable for data professionals aiming to improve their operational practices.
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By Juan Manuel Perafan🎙️ Travis Dent: Data Engineer at Xebia
In this episode, Travis, an experienced professional in data engineering and DevOps, shares his journey from robotics to data analytics. The discussion covers the importance of DevOps practices in data projects, addressing challenges like long-running pipelines and changing data schemas. Travis emphasizes the cultural aspects of DevOps, including collaboration, automation, and continuous improvement, while also touching on different levels of DevOps knowledge for data professionals.
The conversation explores how project management and clear vision contribute to successful data initiatives. Travis and the host discuss how the data field can learn from other industries like aviation and construction, particularly reliability and alerting. The episode concludes with practical recommendations for listeners looking to enhance their DevOps skills, including book suggestions and online resources, making it valuable for data professionals aiming to improve their operational practices.