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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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Unstructured data management and governance using AWS AI/ML and analytics services

AWS Big Data

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. You can integrate different technologies or tools to build a solution.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

Admittedly, it’s still pretty difficult to visualize this difference. In terms of scale, if a PB is the size of the Earth, an EB would be the size of the sun, according to Backblaze – and, if you recall from science class, it takes about 1.3 Here is how Cloudera visualizes and controls the data lifecycle.

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Five Strategies to Accelerate Data Product Development

Cloudera

Once we have identified those capabilities, the second article explores how the Cloudera Data Platform delivers those prerequisite capabilities and has enabled organizations such as IQVIA to innovate in Healthcare with the Human Data Science Cloud. . Business and Technology Forces Shaping Data Product Development.

Strategy 114
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AML: Past, Present and Future – Part III

Cloudera

Support machine learning (ML) algorithms and data science activities, to help with name matching, risk scoring, link analysis, anomaly detection, and transaction monitoring. Provide audit and data lineage information to facilitate regulatory reviews. Spark also enables data science at scale. Cloudera Enterprise.

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Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.