Our guest this week is Tim Miller, from Teradata’s Technology & Innovation Office. He was a principal in the development of the first commercial in-database data mining system, which makes him a perfect choice to provide an <g class="gr_ gr_994 gr-alert gr_gramm gr_inline_cards gr_run_anim Grammar only-ins replaceWithoutSep" id="994" data-gr-id="994">overview</g> of the data science process.

New to data science? There may be occasional bouts of jargon you don’t understand. If so, don’t worry! Tim (naturally) uses terminology from the data science domain, but we always bring it back to plain-English explanations.

• What is data science?
• CRISP-DM: <g class="gr_ gr_6 gr-alert gr_gramm gr_inline_cards gr_run_anim Grammar only-ins doubleReplace replaceWithoutSep" id="6" data-gr-id="6">Cross-industry</g> standard process for data mining [Wikipedia]
• Fundamental: What is the business problem we’re trying to address?
• Data science is a team sport
• Supervised and unsupervised learning
• How do you decide which techniques and algorithms to use?
• What is analytics ops?
• Happiness is “in-platform analytics”