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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Visualizations: past, present, and future.

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

Sisense

“We get access, post-Games, to the ticket data to analyze any patterns in terms of incidents and responses.”. Descriptive analytics also help them understand the number of athletes and workers required to support that specific competition or sport.