Data Engineering Podcast


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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14 October 2021

How And Why To Become Data Driven As A Business - E229

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Summary

Organizations of all sizes are striving to become data driven, starting in earnest with the rise of big data a decade ago. With the never-ending growth in data sources and methods for aggregating and analyzing them, the use of data to direct the business has become a requirement. Randy Bean has been helping enterprise organizations define and execute their data strategies since before the age of big data. In this episode he discusses his experiences and how he approached the work of distilling them for his book "Fail Fast, Learn Faster". This is an entertaining and enlightening exploration of the business side of data with an industry veteran.

Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
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  • Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription
  • Your host is Tobias Macey and today I’m interviewing Randy Bean about his recent book focusing on the use of big data and AI for informing data driven business leadership

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you start by discussing the focus of the book and what motivated you to write it?
    • Who is the intended audience, and how did that inform the tone and content?
  • Businesses and their officers have been aiming to be "data driven" for years. In your experience, what are the concrete goals that are implied by that term?
    • What are the barriers that organizations encounter in the pursuit of those goals?
    • How have the success rates (real and imagined) shifted in recent years as the level of sophistication of the tools and industry for data management has increased?
  • What is the state of data initiatives in leading corporations today?
  • What are the biggest opportunities and risks that organizations focus on related to their use of data?
  • At what level(s) of the organization do lessons around data ethics need to be embedded?
  • You have been working with large companies for many years to help them with their adoption of "big data". How has your work on this book shifted or clarified your perspectives on the subject?
  • What are the main lessons or ideas that you hope readers will take away from the book?
  • What are the most interesting, innovative, or unexpected ways that you have seen big data applied to business?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on this book?
  • What are your predictions for the next decade of big data and AI?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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