article thumbnail

Speed up queries with the cost-based optimizer in Amazon Athena

AWS Big Data

Doing it before risks unnecessary aggregation overhead because each value is likely unique anyway and that step will not result in an earlier reduction in the amount of data transferred between intermediate stages. Analytics Architect on Amazon Athena. He has been working on query optimizers for over a decade.

article thumbnail

Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

IT leaders adjust budget priorities as economic outlook shifts

CIO Business Intelligence

Security tops the list According to this year’s State of the CIO survey , cybersecurity and risk management are the top investment areas for 45% of IT leader respondents. Focus on risk management, he advises, and “have a little faith in your CFO and CEO. Another investment area includes tools given to sales agents.

IT 132
article thumbnail

Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

What are the projected risks for companies that fall behind for internal training in data science? What’s a reasonably good persona to target for employees who want training in data science to shift into new roles? They use data infrastructure at work. In business terms, why does this matter ? That’s no problem.

article thumbnail

Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Consider the following timeline: 2001 – Physics grad students are getting hired in quantity by hedge funds to work on Wall St. to join data science teams, e.g., to support advertising, social networks, gaming, and so on—I hired more than a few. 2018 – Global reckoning about data governance, aka “Oops!