Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Executive Briefing: Analytics for executives—Building an approachable language to drive data science in your organization

Brandy Freitas (Pitney Bowes)
1:10pm–1:50pm Thursday, 09/13/2018
Data-driven business management, Strata Business Summit
Location: 1E 14 Level: Non-technical
Secondary topics:  Machine Learning in the enterprise, Transportation and Logistics
Average rating: ****.
(4.50, 6 ratings)

Who is this presentation for?

  • Everyone will find value in this session.

What you'll learn

  • Develop a common, approachable language to effectively communicate the importance of, findings from, and innovations in data science

Description

Data science has the power to change the world around us, drive businesses forward, and answer some of the most pressing questions in modern research. Often, however, we miss the mark on fully integrating data science into organizations due to misunderstanding, miscommunication, and misconception of what data science can actually do.

To bring data science into the forefront of our business strategies effectively, we all need to be speaking the same language. Because there must be participation and input from all sources, from the C-suite to the analyst, we cannot continue to obfuscate through complicated tech talk, nor should we boil down elegant solutions so that they barely resemble what they actually are. Finding a common ground is critical in moving data science forward in all industries.

Join Brandy Freitas to develop context and vocabulary around data science topics—a Rosetta Stone of sorts to enable managers and executives to confidently and informatively speak with their data scientists and analysts and, equally importantly, allow data scientists to speak with their less technical colleagues, helping build a culture of data within your organization.

Topics include:

  • Developing language around data science and analytics from a nontechnical standpoint, including supervised and unsupervised learning techniques
  • How to ask questions in an analytical way
  • Demystifying the vocabulary around tools that data scientists use in analysis
  • Big data: What is it, and how do I know if I have it? What can it do for my industry? How can I explain its value to my colleagues and company leadership?
  • Hiring: Where do I find data scientists, and what kinds of skills are really important in growing my group? What kind of language should I use in seeking applicants?
  • Deep learning: When is it appropriate to use, and what are its practical advantages? What kind of questions can I solve using deep learning, and how would I communicate this to my staff or my stakeholders?
Photo of Brandy Freitas

Brandy Freitas

Pitney Bowes

Brandy Freitas is a principal data scientist at Pitney Bowes, where she works with clients in a wide variety of industries to develop analytical solutions for their business needs. Brandy is a research physicist-turned-data scientist based in Boston, MA. Her academic research focused primarily on protein structure determination, applying machine learning techniques to single-particle cryoelectron microscopy data. Brandy is a National Science Foundation Graduate Research Fellow and a James Mills Pierce Fellow. She holds an undergraduate degree in physics and chemistry from the Rochester Institute of Technology and did her graduate work in biophysics at Harvard University.

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Comments

Thomas Roach | SYSTEMS ENGINEER
09/25/2018 6:14am EDT

Can you please upload the slides? Thanks!

Alan Schiemenz | DATA SCIENCE MANAGER
09/18/2018 5:35am EDT

Are the slides available for this talk?