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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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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making. XLSTAT is an Excel data analysis add-on geared for corporate users and researchers. Analytics, Data Science

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

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Delivering Low-latency Analytics Products for Business Success

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

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Using visualizations to make smarter decisions.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels.