What Is Augmented Analytics?

Written by Indicative Team


Augmented Analytics Defined

Augmented analytics is the combination of machine learning (ML) and natural language processing (NLP) to enhance analytics, data sharing and business intelligence.

This type of analytics works by, scrubbing, parsing and returning raw data to organisations for analysis.

By combining ML and NLP for analyzing large sets of data, the process can be automated, reducing time consuming tasks such as data collection and preparation. It also creates data democratization, by communicating data insights to colleagues, executives and shareholders with ease. It also allows for businesses to understand and interact with data organically, allowing for the notice of valuable or unusual trends.

Augmented analytics allows business to;

  • Achieve deeper data analysis – it can pinpoint which factors are truly influencing a businesses outputs
  • Receive insights faster – it allows insights in a matter of seconds
  • Better utilize resources and
  • Gain actionable insights

Overall, augmented analytics allows businesses to assess their performance, identify growth opportunities and gain a holistic understanding of where a business stands competitively in the market, contributing to a solid business strategy.

In Data Defined, we help make the complex world of data more accessible by explaining some of the most complex aspects of the field.

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