Finding (and Sharing) Your Internal Data Pain Points - Interview w/ Molly Vorwerck

Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB) In this episode, Scott interviews Molly Vorwerck, head of content and communications at data observability vendor Monte Carlo. Scott asked Molly to be on as she is a great community member in general and as Monte Carlo is well known in the data space for putting out high quality content on hot-button issues. The idea is to take how Molly and team get their ideas and apply that process to figuring out major pain points internally and creating a cohesive strategy to at least start discussing them. Molly recommends to constantly be interviewing stakeholders. She talks about interviewing people from multiple sides of a challenge, e.g. not just the data consumers but the data producers and the data engineering teams re data challenges. She tries to give people the space to tell their story and asks open-ended questions to truly get their perspective, not arrive at a pre-specified answer. Molly talks about ways to make the other person feel valued by active listening and making the conversation mutually beneficial. It may be a person you want to interview again so building the relationship is crucial, not just extracting info in a one-time manner. Scott and Molly dig a bit into the idea of blameless post mortems and how valuable they can be for doing data mesh, especially to figure out what happened to cause data downtime and how to prevent the same issue in the future. Molly's LinkedIn: https://www.linkedin.com/in/vorwerck/ (https://www.linkedin.com/in/vorwerck/) Monte Carlo's blog: https://www.montecarlodata.com/blog/ (https://www.montecarlodata.com/blog/) Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him at community at datameshlearning.com or on LinkedIn: https://www.linkedin.com/in/scotthirleman/ (https://www.linkedin.com/in/scotthirleman/) If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshl