article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

article thumbnail

The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games. “We We get access, post-Games, to the ticket data to analyze any patterns in terms of incidents and responses.”.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

How to supercharge data exploration with Pandas Profiling

Domino Data Lab

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Additionally, the Python ecosystem is flush with open source development projects that maintain the language’s relevancy in the face of new techniques in the field of data science. ref: [link]. ref: [link].

article thumbnail

Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive.