Data engineers are responsible for building tools and platforms to power the workflows of other members of the business. Each group of users has their own set of requirements for the way that they access and interact with those platforms depending on the insights they are trying to gather. Benn Stancil is the chief analyst at Mode Analytics and in this episode he explains the set of considerations and requirements that data analysts need in their tools and. He also explains useful patterns for collaboration between data engineers and data analysts, and what they can learn from each other.
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- Your host is Tobias Macey and today I’m interviewing Benn Stancil, chief analyst at Mode Analytics, about what data engineers need to know when building tools for analysts
- How did you get involved in the area of data management?
- Can you start by describing some of the main features that you are looking for in the tools that you use?
- What are some of the common shortcomings that you have found in out-of-the-box tools that organizations use to build their data stack?
- What should data engineers be considering as they design and implement the foundational data platforms that higher order systems are built on, which are ultimately used by analysts and data scientists?
- In terms of mindset, what are the ways that data engineers and analysts can align and where are the points of conflict?
- In terms of team and organizational structure, what have you found to be useful patterns for reducing friction in the product lifecycle for data tools (internal or external)?
- What are some anti-patterns that data engineers can guard against as they are designing their pipelines?
- In your experience as an analyst, what have been the characteristics of the most seamless projects that you have been involved with?
- How much understanding of analytics are necessary for data engineers to be successful in their projects and careers?
- Conversely, how much understanding of data management should analysts have?
- What are the industry trends that you are most excited by as an analyst?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
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