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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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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

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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.