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‘Augmented Analytics’ an advanced approach to data analysis

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Posted on Oct 14, 2019
by Dev Kumbhare ( Sr. Manager Business Development)

‘Augmented Analytics’ an advanced approach to data analysis

Just a few days ago, a Gartner report revealed five major trends sharing the evolution of analytics and business intelligence, namely

a)    Augmented Analytics

b)    Digital Culture

c)    Relationship Analytics

d)    Decision intelligence

e)    Operationalizing and Scaling

As data is growing exponentially and with businesses requiring a number of skilled data science experts to process this vast amount of data to derive meaningful information, they are now realizing the importance of artificial intelligence and machine learning that helps speed up data processing. However, to solve more complex problems data scientists are turning to Augmented Analytics which helps automate the data insights by utilizing machine learning and natural language generation for automating data preparation, data discovery, and insight sharing. As a result, data scientists can avoid wasting time digging through data, and instead utilize their expertise to maximum value and drive performance.

Gartner has cited augmented analytics as “the next wave of disruption in the data and analytics market that leaders should plan to adopt.”

The global augmented analytics market size was valued at $4,094 million in 2017 and is projected to reach $29,856 million by 2025, growing at a CAGR of 28.4% from 2018 to 2025.

The key players operating in the global augmented analytics market analysis include IBM Corporation, Qlik, Tableau Software, Tibco Software, Salesforce, Sisense Inc., SAP SE, SAS Institute, Microsoft, and ThoughtSpot.

Deploying augmented analytics solutions, world-wide organizations have realized two key benefits

  • Faster results: Augmented analytics automates various steps involved in data analysis, thereby helping in achieving fast outcomes which can be easily interpreted thereby saving time to get those meaningful insights.
  • Valuable and meaningful insights: Augmented analytics can go beyond the traditional reporting and could dig deeper for insights and exploring hidden trends and patterns. It can study several datasets in combination and reveal hitherto unknown correlations.

To conclude, although augmented analytics is still in its infancy, many experts suggest its growth will be quick and will be the logical next step of analytics applications. Machine learning and natural language processing provide a deep well of opportunity to pull insights from analytics. The quicker you adapt to this technology, the sooner your team will be able to find and exploit growth opportunities compared to their competition. Finally, we will see more and more businesses of all sizes using and benefiting from analytics in the years to come. To get more insights into this concept, visit

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Category: Data Analytics, RPA & AI

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