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Augmented analytics

Dataconomy

Augmented analytics is revolutionizing how organizations interact with their data. By harnessing the power of machine learning (ML) and natural language processing (NLP), businesses can streamline their data analysis processes and make more informed decisions. What is augmented analytics?

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Leveraging third-party data : Incorporating external data sources, such as weather, social media trends, and market reports, enriches your analysis, providing a more comprehensive understanding of customer behavior and market dynamics. AI and augmented analytics assist users in navigating complex data sets, offering valuable insights.

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Data Audit in the Age of Machine Learning: Goals and Challenges

Dataversity

Despite its many benefits, the emergence of high-performance machine learning systems for augmented analytics over the last 10 years has led to a growing “plug-and-play” analytical culture, where high volumes of opaque data are thrown arbitrarily at an algorithm until it yields useful business intelligence.

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What Is Data Intelligence?

Alation

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.