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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. It is frequently used for risk analysis.

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Citizen Data Scientists Are Key. So Is the Solution They Use.

Smarten

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If

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3 Things Citizen Data Scientists Need in Predictive Analytics!

Smarten

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Descriptive Statistics. Access to Flexible, Intuitive Predictive Modeling. Forecasting.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. What is the point of those obvious statistical inferences? How does that work in practice?

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. 4) Predictive And Prescriptive Analytics Tools.