Every organization needs to be able to use data to answer questions about their business. The trouble is that the data is usually spread across a wide and shifting array of systems, from databases to dashboards. The other challenge is that even if you do find the information you are seeking, there might not be enough context available to determine how to use it or what it means. Castor is building a data discovery platform aimed at solving this problem, allowing you to search for and document details about everything from a database column to a business intelligence dashboard. In this episode CTO Amaury Dumoulin shares his perspective on the complexity of letting everyone in the company find answers to their questions and how Castor is designed to help.
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- Your host is Tobias Macey and today I’m interviewing Amaury Dumoulin about Castor, a managed platform for easy data cataloging and discovery
- How did you get involved in the area of data management?
- Can you describe what Castor is and the story behind it?
- The market for data catalogues is nascent but growing fast. What are the broad categories for the different products and projects in the space?
- What do you see as the core features that are required to be competitive?
- In what ways has that changed in the past 1 – 2 years?
- What are the opportunities for innovation and differentiation in the data catalog/discovery ecosystem?
- How do you characterize your current position in the market?
- Who are the target users of Castor?
- Can you describe the technical architecture and implementation of the Castor platform?
- How have the goals and design changed since you first began working on it?
- Can you talk through the workflow of getting Castor set up in an organization and onboarding the users?
- What are the design elements and platform features that allow for serving the various roles and stakeholders in an organization?
- What are the organizational benefits that you have seen from users adopting Castor or other data discovery/catalog systems?
- What are the most interesting, innovative, or unexpected ways that you have seen Castor used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Castor?
- When is Castor the wrong choice?
- What do you have planned for the future of Castor?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Monte Carlo
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