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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 a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist salary. Semi-structured data falls between the two.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

Data engineers also need communication skills to work across departments and to understand what business leaders want to gain from the company’s large datasets. Data engineers must also know how to optimize data retrieval and how to develop dashboards, reports, and other visualizations for stakeholders.

Analytics 135
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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 130
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8 tips for unleashing the power of unstructured data

CIO Business Intelligence

Making the most of enterprise data is a top concern for IT leaders today. With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides.

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The Future Is Hybrid Data, Embrace It

Cloudera

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. Where data flows, ideas follow.

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