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Data Analytics: The Four Approaches to Analyzing Data and How To Use Them Effectively

KDnuggets

You will learn about descriptive analytics, data warehousing, machine learning, and big data.

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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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Master the Power of Data Analytics: The Four Approaches to Analyzing Data

KDnuggets

Learn about descriptive analytics, data warehousing, machine learning, and big data.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What is data analytics? Data analytics is a discipline focused on extracting insights from data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. What are the four types of data analytics?

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What are the benefits of business analytics? What is the difference between business analytics and data analytics?

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Improve Underwriting Using Data and Analytics

Cloudera

To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. Simply stated, this approach enables data to be collected from any location and reside in any location for analytics to then be performed. Step two: expand machine learning and AI.

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Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process.