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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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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? Data analytics and data science are closely related.

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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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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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4 imperatives for making business intelligence work

O'Reilly on Data

They recognize the instrumental role data plays in creating value and see information as the lifeblood of the organization. The business intelligence (BI) and data science industries have spent the last couple decades making data access easier, analytic capability more comprehensive, and platforms more scalable.

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

Smart Data Collective

Here are some of the disadvantages of using Python as data preprocessing technology: Python’s memory consumption is high. It is a dynamically typed language where some machine learning or data science fields prefer Statically Typed programming languages. Python Makes Decision Making Simple.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.