How And Why To Become Data Driven As A Business
Data Engineering Podcast
What's the Difference Between a Book and an Article?
The author says he wanted to educate a broader audience of general users on why data really matters and why it matters. The book also aims to reach senior business decision makers who often see data as just another project o, something that should be pushed off to the corner. Andthe lastly, i wanted to write for the practitioners, and that's why? I pulled together roughly 25 case studies from leading fortune one thousand companies to show how leading companies ere approaching various issues around data management and analytics.
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
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- 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
- @RandyBeanNVP on Twitter
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
- Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI (affiliate link)
- Harvard Business Review
- MIT Sloan Review
- New Vantage Partners
- COBOL
- Moneyball
- Weapons of Math Destruction
- The Seven Roles of the Chief Data Officer
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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