Big Data and augmented analytics

By: Bank of Baroda
Fri Oct 23, 2020
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Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, exploration and analysis in BI platforms.

Augmented analytics integrate AI elements into the analytics and BI process to help users prepare their data, discover new insights and easily share them with stakeholders in the organization.

Augmented analytics is an emerging technology that deals with data and analytics with the application of machine learning along with NLP to automate data preparation, insight discovery and insight sharing across a broad range of business users. Augmented analytics is applied to enhance data analytics, data sharing and business intelligence that marks the next wave of disruption in the data and analytics market

The Augmented Analytics Market size is expected to grow from USD 4.8 billion in 2018 to USD 18.4 billion by 2023, at a CAGR of 30.6%.

The adoption of augmented analytics has increased exponentially due to the integration of natural language processing technology that allows business intelligence technology users to interact in a conversational mode. The technology also provides a recommendation on methods to use and enrich data for in-depth analysis.

The major vendors operating in the augmented analytics market include Salesforce, SAP, IBM, Oracle and Microsoft. Major growth drivers for the market are increasing volume of complex data and growing adoption of advanced business analytics tools.

The adoption of Big Data across the retail sector has led to an increase in the adoption rates of Augmented Analytics. According to SAS Institute, estimated adoption rates of Big Data in the United Kingdom in 2020 is forecasted at around 59%. This showcases the huge potential for augmented analytics and thus, can provide a great advantage in the online retail segment.

Data and analytics professionals are adopting the application of augmented analytics with platform capabilities into their existing business models.

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