How to Whisper to Data (and Executives) | Scott Taylor on The Artists of Data Science Podcast

Some notable segments from the show:

[10:08] What separates great data scientists from good ones

Where to listen to the show

Listen to the episode on Apple Podcasts, Spotify, Overcast, Stitcher, Castbox, Google Podcasts, TuneIn, YouTube, or on your favorite podcast platform.

Scott’s journey into data

Scott has been working in the data space for a couple of decades. His first role working with data was working for an organization where he is looking at location data about supermarkets. Before then, he worked in consumer promotion, where he was never quite satisfied. He is happy to be working with data, and helping people tell their data story.

Where is the field headed in 2–5 years?

Scott tells us that the core value of the content is not going to change to the point where it is unrecognizable. Big data needs highly structured content to work. Regardless of what happens in A.I. and machine learning in the next few years, companies will still need highly structured data.

What will separate great data scientists from the rest of them?

Scott tells us what separates the great data scientists from the merely good ones is the ability to manage and govern core data assets. People tend to focus on the cool and sexy stuff. But if you build upon a weak foundation, it’s going to fall. Great data scientists build a foundation and are better equipped for long term success. It’s not all about the latest data science thing you’re doing, because you can’t do that at scale unless you’ve got great data.

Key takeaways from the episode

The eight ‘ates of master data

Hear Scott go deep on the eight ‘ates at the [12:57] mark.

Tips on communicating with executives

[17:04] Focus on the results from your findings. As proud as you might be about your algorithms and about all the mistakes you made that you fixed to get here, that executive team doesn’t care about that. You need to tie your results to some recommended action. Ask yourself, “how is my insight that I created or the opportunity that I discovered going to move the business forward?”

Legacy systems in a start-up

[21:43] Start-ups have the advantage of not having legacy systems. If you’ve got a set of data that you’re working with that’s becoming the standard for your organization, make sure you share that. Try to form consensus around some form of standards as early as you can.

Important soft skills

[28:14] You need to know how to communicate and listen effectively. You need to be able to communicate your idea through a story. I advise people to take a sales course, because that’s how you learn how to tell a great story with empathy, emotion, and emphasis.

People who think they don’t belong in data science

[29:58] You need to find your passion in data. Data science is the hottest space to be in, and that isn’t an original opinion. Data science can help businesses grow, improve, and protect themselves. I don’t think you need to do it all, but find your niche and find your expertise and then run with it. There is a lot of opportunities in this space.

Memorable quotes

The one thing that Scott wants you to learn from his story

[33:08] Remember the value, the foundational importance, the critical nature of master data. It is the most important data any organization has.

From the lightning round

The best advice Scott has ever received

“When you walk into a sales call, never give them the magazine.” What that means is, customers can’t listen and look at a product simultaneously. They can’t focus on two things at once.

What motivates Scott

Doing fun stuff. I love the reaction I get from people from my crazy stuff.

Advice that Scott would give to his 18 year old self

Get focused, and recognize where your true strengths are.

The book Scott recommends you to check out

“Big Data, Big Dupe: A Little Book about a Big Bunch of Nonsense ” by Stephen Few

Where to find Scott online

LinkedIn

Episode Transcript

You are welcome to share the below transcript (up to 500 words) in media articles (e.g., The New York Times, LA Times, The Guardian), on your personal website, in a non-commercial article or blog post (e.g., Medium), and/or on a personal social media account for non-commercial purposes, provided that you include attribution to “The Artists of Data Science” and link back to the https://theartistsofdatascience.fireside.fm/articles URL.

Full episode on YouTube

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The Artists of Data Science

The Artists of Data Science

The ONLY personal development podcast for data scientists.