The primary application of data has moved beyond analytics. With the broader audience comes the need to present data in a more approachable format. This has led to the broad adoption of data products being the delivery mechanism for information. In this episode Ranjith Raghunath shares his thoughts on how to build a strategy for the development, delivery, and evolution of data products.
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- Your host is Tobias Macey and today I'm interviewing Ranjith Raghunath about tactical elements of a data product strategy
- How did you get involved in the area of data management?
- Can you describe what is encompassed by the idea of a data product strategy?
- Which roles in an organization need to be involved in the planning and implementation of that strategy?
- order of operations:
- strategy -> platform design -> implementation/adoption
- platform implementation -> product strategy -> interface development
- managing grain of data in products
- team organization to support product development/deployment
- customer communications - what questions to ask? requirements gathering, helping to understand "the art of the possible"
- What are the most interesting, innovative, or unexpected ways that you have seen organizations approach data product strategies?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on defining and implementing data product strategies?
- When is a data product strategy overkill?
- What are some additional resources that you recommend for listeners to direct their thinking and learning about data product strategy?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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