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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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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.

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Machine Learning and AI Underpin Predictive Analytics to Achieve Clinical Breakthroughs

Cloudera

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. One of the downsides of the role that data now plays in the modern business world is that users can be overloaded with jargon and tech-speak, which can be overwhelming.

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

AWS Big Data

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

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Introducing Cloudera DataFlow (CDF)

Cloudera

Flow Management – Adopt a no-code approach to create visual flows for building complex data ingestion / transformation with drag-and-drop ease. Powered by Apache NiFi and its 260+ pre-built processors, CDF enables you to take on extremely high-scale, high-volume and high-speed data ingestion use cases with simplicity and ease.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. Coding skills – SQL, Python or application familiarity – ETL & visualization? Does Data warehouse as a software tool will play role in future of Data & Analytics strategy?