The Data Exchange Podcast: Jesse Anderson, Ben Lorica, and Jenn Webb on tools, processes, and best practices for building high-impact data applications.
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In this episode of the Data Exchange, our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Jesse Anderson, Managing Director at the Big Data Institute. Jesse is the author of a recent book entitled “Data Teams: A Unified Management Model for Successful Data-Focused Teams”.
We discussed a range of topics including:
- How do you set up your data teams?
- How do you make sure that teams are successful? What sort of training programs should you have available for your teams?
- How do you make sure your data teams work with key stakeholders?
- Recent progress in tools for data engineers and data architects, including distributed systems, streaming frameworks, and new tools for building and managing data pipelines.
Jesse has extensive experience as an engineer and architect and he has consulted and trained data engineering teams across many companies and industries. He has helpd implement streaming and real-time systems, and over the past few years Jesse has loved what is coming out of the Apache Pulsar community:
- We also have advances in the Apache Pulsar community, we’re seeing some really cool features around that with Pulsar functions. With Pulsar our functions they are removing some of that operational onus of teams having to deal with questions like: Where do I run this? How do I run this? How do I keep all this boilerplate code out? This is something that is better done as a Lambda function, if you’re familiar with that. Pulsar functions are like AWS Lambda functions, except they run on Pulsar. Companies also have some some of the operational issues with tiered storage or with multi-tenancy, those sorts of things are being solved better with Pulsar.
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Related content:
- A video version of this conversation is available on our YouTube channel.
- Responsible AI in Practice: fantastic talks and discussion in this recent webinar, video is now available for FREE on-demand.
- Ameet Talwalkar: “Democratizing Machine Learning”
- Denise Gosnell: “How graph technologies are being used to solve complex business problems”
- Christopher Nguyen: “Designing machine learning models for both consumer and industrial applications”
- Wes McKinney: “Improving performance and scalability of data science libraries”
- Alan Nichol: “Best practices for building conversational AI applications”
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