This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
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Brief Conversations From The Open Data Science Conference: Part 1 - Episode 30
Summary
The Open Data Science Conference brings together a variety of data professionals each year in Boston. This week’s episode consists of a pair of brief interviews conducted on-site at the conference. First up you’ll hear from Alan Anders, the CTO of Applecart about their challenges with getting Spark to scale for constructing an entity graph from multiple data sources. Next I spoke with Stepan Pushkarev, the CEO, CTO, and Co-Founder of Hydrosphere.io about the challenges of running machine learning models in production and how his team tracks key metrics and samples production data to re-train and re-deploy those models for better accuracy and more robust operation.
Preamble- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and this week I attended the Open Data Science Conference in Boston and recorded a few brief interviews on-site. First up you’ll hear from Alan Anders, the CTO of Applecart about their challenges with getting Spark to scale for constructing an entity graph from multiple data sources. Next I spoke with Stepan Pushkarev, the CEO, CTO, and Co-Founder of Hydrosphere.io about the challenges of running machine learning models in production and how his team tracks key metrics and samples production data to re-train and re-deploy those models for better accuracy and more robust operation.
- What are the challenges of gathering and processing data from multiple data sources and representing them in a unified manner for merging into single entities?
- What are the biggest technical hurdles at Applecart?
- @alanjanders on Twitter
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Spark
- DataBricks
- DataBricks Delta
- Applecart
- What is Hydropshere.io?
- What metrics do you track to determine when a machine learning model is not producing an appropriate output?
- How do you determine which data points to sample for retraining the model?
- How does the role of a machine learning engineer differ from data engineers and data scientists?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Hydrosphere
- Machine Learning Engineer
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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