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Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...

Editor’s note: This is the third article in a four-part series that is part of a larger initiative the AICPA Auditing Standards Board (ASB) has undertaken to understand and support technology use in ...

LASIK offers an example of how ophthalmology is becoming data-driven, using advanced imaging to move beyond static ...

Effective data governance requires a mindset that treats data as an asset, which is just as important as a physical “sticks and bricks” asset with a life cycle. The drivers behind this change include ...

Researchers may refer to this guidance when determining how to handle the collected research data from human subjects, and what steps need to be taken after data collection is complete. Updated: 02.02 ...

The film details the data analysis procedures used in a comparative psycholinguistics research project at the University of Illinois, initiated in 1960. It illustrates the systematic steps taken to ...

The Pentagon wants to make it easier for its organizations to use data analytics, so it’s overhauling its Advana platform to pull data from disparate sources instead of pooling it in one place. Users ...

Tableau, TIBCO Data Science, IBM and Sisense are among the best software for predictive analytics. Explore their features, pricing, pros and cons to find the best option for your organization.

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...