Emily Gorcenski, Data & AI Service Line Lead at Thoughtworks, joins Corey on Screaming in the Cloud to discuss how big data is changing our lives - both for the better, and the challenges that come with it. Emily explains how data is only important if you know what to do with it and have a plan to work with it, and why it’s crucial to understand the use-by date on your data. Corey and Emily also discuss how big data problems aren’t universal problems for the rest of the data community, how to address the ethics around AI, and the barriers to entry when pursuing a career in data. About EmilyEmily Gorcenski is a principal data scientist and the Data & AI Service Line Lead of ThoughtWorks Germany. Her background in computational mathematics and control systems engineering has given her the opportunity to work on data analysis and signal processing problems from a variety of complex and data intensive industries. In addition, she is a renowned data activist and has contributed to award-winning journalism through her use of data to combat extremist violence and terrorism. The opinions expressed are solely her own.Links Referenced:
ThoughtWorks: https://www.thoughtworks.com/

Personal website: https://emilygorcenski.com

Twitter: https://twitter.com/EmilyGorcenski

Mastodon: https://mastodon.green/@emilygorcenski@indieweb.social

TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. My guest today is Emily Gorcenski, who is the Data and AI Service Line Lead over at ThoughtWorks. Emily, thank you so much for joining me today. I appreciate it.Emily: Thank you for having me. I’m happy to be here.Corey: What is it you do, exactly? Take it away.Emily: Yeah, so I run the data side of our business at ThoughtWorks, Germany. That means data engineering work, data platform work, data science work. I’m a data scientist by training. And you know, we’re a consulting company, so I’m working with clients and trying to help them through the, sort of, morphing landscape that data is these days. You know, should we be migrating to the cloud with our data? What can we migrate to the cloud with our data? Where should we be doing with our data scientists and how do we make our data analysts’ lives easier? So, it’s a lot of questions like that and trying to figure out the strategy and all of those things.Corey: You might be one of the most perfectly positioned people to ask this question to because one of the challenges that I’ve run into consistently and persistently—because I watch a lot of AWS keynotes—is that they always come up with the same talking point, that data is effectively the modern gold. And data is what unlocks value to your busin—“Every business agrees,” because someone who’s dressed in what they think is a nice suit on stage is saying that it’s, “Okay, you’re trying to sell me something. What’s the deal here?” Then I check my email and I discover that Amazon has sent me the same email about the same problem for every region I’ve deployed things to in AWS. And, “Oh, you deploy this to one of the Japanese regions. We’re going to send that to you in Japanese as a result.”And it’s like, okay, for a company that says data is important, they have no idea who any of their customers are at this point, is that is the takeaway here. How real is, “Data is important,” versus, “We charge by the gigabyte so you should save all of your data and then run expensive things on top of it.”Emily: I think data is very important, if you know what you’re going to do with it and if you have a plan for how to work with it. I think if you look at the history of computing, of te