Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Principles of data science management

David Martinez Rego (DataSpartan)
14:0514:45 Thursday, 25 May 2017
Data-driven business management
Location: Capital Suite 17
Level: Non-technical
Average rating: **...
(2.50, 4 ratings)

Who is this presentation for?

  • Managers, directors, lead data scientists, and ML practitioners

Prerequisite knowledge

  • Basic knowledge of math and statistics

What you'll learn

  • Understand commonly encountered recipes in data science literature and folklore regarding feature extraction, algorithm selection, evaluation, etc. from a theoretical point of view
  • Explore correct procedures in order to prevent most common pitfalls in the management of data science


Data science lies at the intersection of a number of disciplines, including mathematics, computer science, statistics, and communications. The overwhelming breadth of its body of knowledge makes it difficult for businesses and practitioners to effectively communicate results and challenges, manage the lifecycle of data-driven projects, build a technology radar that allows for opportunity discovery, manage the uncertainty of data science projects, or select the correct set of human resources and technologies.

Despite being a largely experimental discipline, data science is built on a set of solid foundations, such as learning theory, that have traditionally been restricted to the academic setting due to their theoretical nature. The growth of data science as a strategic discipline makes its correct management paramount to the survival of new and traditional businesses that want to compete in a foreseeable data-driven economy. David Martinez Rego shares a set of sound, solid principles (that should be familiar to any data science manager) that will help increase your effectiveness as a data science manager, anticipate limitations of algorithms and overcome them, and assist in understanding each current and future technique or algorithm into a broader context.

Photo of David Martinez Rego

David Martinez Rego


David Martinez Rego is a data scientist at DataSpartan specializing in designing tailored software systems and algorithms. He has been part of laboratories in a number of academic institutions, including the University of A Coruña, the University of Florida, and University College London. Currently, he is based in London, where he divides his time doing research, lecturing, and consulting for different industries and startups.

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13/06/2017 15:01 BST

Dear David,

Thank you for your interesting presentation and insights.
Is it possible to get the slides or keynotes from your session?
Thank you