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Analytics-First Business Strategy

by | Buying BI, Podcast

Ad Hoc Endowment Reporting

Data Talks, Episode 12

Data Talks is Exago’s podcast on all-things business intelligence, analytics, and application software. This month, Booz Allen Hamilton principal data scientist and executive advisor Kirk Borne explains “analytics-first” business strategy (not to be confused with data-first business strategy). We learn what it takes for businesses to begin doing data science and hear about companies who have found success in asking the right questions and establishing a culture of curiosity around analytics. 

Timestamps 

Segment 1: Analytics-First Business Strategy

(1:10) Meet Kirk, an astrophysicist-turned-data scientist.

(4:40) On data science (“computational informatics”) at George Mason University.

(9:00) On advocating for data literacy in the workplace.

(14:00) Understanding statistical claims.

(19:00) What it means to put analytics first.

(22:40) Signs your company is not analytics-first.

(27:00) Qualities of a good data scientist.

(27:40) Fostering a learning culture in the workplace.

(29:10) On unconventional data science hires.

(32:20) Analytics Case Study #1: Web Traffic Analysis

(36:00) Analytics Case Study #2: Date Details

(38:30) “Proofs of Value” vs “Proofs of Concept”

(41:20) The minimum companies need to get started with data science.

Segment 2: What We Are Nerding Out About

(45:24) Kirk: Edge analytics and 4D printing, (especially nanotubes)!

(51:40) Nicole: Gource, a free version control visualization tool!

(53.20) Travis: Ultimate frisbee analytics!

 

Featured Guest 

Kirk Borne headshot

Kirk Borne is Principal Data Scientist and Executive Advisor at Booz Allen Hamilton. He helped establish data science as a discipline during his tenure as Professor of Astrophysics and Computational Science at George Mason University and also helped found the field of Astroinformatics. His influence in the data space has made him a highly sought-after public speaker and top-ranking thought leader in data analytics, machine learning, and martech.

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