Ever wondered how to turn data into actionable insights? Join us as we sit down with Elena Dyachkova, the head of data at Bubble, who has an impressive background leading data teams at industry giants like Peloton and Spring Health. Elena walks us through her inspiring journey from economics to product analytics, shedding light on the critical role data plays in decision-making. She shares how simple analytics methods can be just as impactful as complex models, making this a must-listen for anyone looking to improve their analytical skills.
Data accuracy and reliability are paramount, especially when working with business applications like Stripe. Elena provides a deep dive into the challenges data teams face, from API changes to schema updates, and stresses the importance of proactive monitoring and observability. We discuss how to build strong heuristics and set realistic expectations with stakeholders to ensure seamless data flows. This segment is packed with practical advice for data professionals looking to navigate the complexities of modern data environments.
Continuous learning is at the heart of effective product analytics. Elena reflects on the evolution of education in this field, pointing out the gap that once existed and how diverse courses on business metrics, growth strategy, and experimentation have filled it. We explore the significance of data collection, structure, and engineer collaboration, all essential for robust product analysis. Elena also discusses the importance of maintaining a mindset geared towards iterative testing and learning, helping you avoid the dreaded analysis paralysis. Don’t miss her references to key figures and literature that have influenced her journey.
Follow Elena on:
- LinkedIn - https://www.linkedin.com/in/edyachkova/
- X - @ElenaRunsNYC
- Substack Blog - Dramatic Analyst
- UpLimit Course - Product Analytics
What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.
