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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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Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. Simply put, data visualization means showing data in a visual format that makes insights easier to understand for human users.

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

CIO Business Intelligence

This can be achieved by utilizing dense storage nodes and implementing fault tolerance and resiliency measures for managing such a large amount of data. First and foremost, you need to focus on the scalability of analytics capabilities, while also considering the economics, security, and governance implications. Focus on scalability.

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Top 10 Analytics Trends for 2019

Timo Elliott

2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.

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How a Discovery Data Warehouse, the next evolution of augmented analytics, accelerates treatments and delivers medicines safely to patients in need

Cloudera

In any pharma, one of the largest data problems is variety, and it has been unsolved for the last 11 years, because: . Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. You can link dashboards and have them depend on each other.