Augmented Analytics vs Business Intelligence

In business, we are in an era where augmented analytics is king. By using complex algorithms, augmented analytics can gain insights into consumer trends and behavior and capitalize this data to strategically place themselves as an organization. This capability thus gives companies using Business Intelligence (BI) a run for their money. According to the Gartner Report, users of analytics platforms powered by augmented data discovery will grow at twice the rate and deliver twice the amount of business value as compared to the competition who is not.

Business intelligence is quite different from augmented analytics. BI seeks to answer the questions: what happened; when it happened; who it concerns, and quantity affected. In contrast, augmented analytics looks to answer the questions: why it happened; will it occur again; what will happen if “x” is changed; and what the data is saying that we missed.Why businesses need to switch to Augmented Analytics 
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Why businesses need to switch to Augmented Analytics

  • Dashboards aren’t enough

Businesses need augmented analytics to make useful tailored insights from all the data coming their way. Instead of just presenting the insights, AA also presents options to further propel the business forward in terms of risk management, problem solving and uncertainties. Since Artificial Intelligence (AI) and Machine Learning (ML) have a wide range of algorithms that can extrapolate full probability distributions, the users can better analyze situations.  For instance, a marketing manager needs insight into how his customers think and in so doing align products to match these needs.

  • Expert shortage

A recent McKinsey report has shown that there is an acute shortage of professionals with critical data analytical skills who can analyze data and make proper decisions therein. Having data experts in every department is crucial. However, even if they are able to do this, having the right software is critical for success.  Augmented analytics enables everyday staff to perform analytical tasks only a specialized data scientist would have. This means that the company will not have to employ more analysts to crunch out data.

  • Real-time insights

Traditionally, there has always been a bottleneck between when data is received and when insights are obtained and acted upon. This is mainly because of the slow pace of analysis the data goes through. With data analytics, data is obtained, analyzed. Sorted and presented as fast as it happens. This means that users only get actionable intelligence in real-time. This makes strategy improvement to be a lot better and accurate.

  • Data overload

Since data is growing at unprecedented rates, going through it traditionally is no longer an option. Mainly because the costs associated with it do not reflect the speed and precision desired. As such, investing in augmented analytics ensures that data is broken down and sifted into manageable insights that actually propel a business into the next level. AA also helps keep standards high and reduces the chances of an oversight thus ensuring quality insights all through.

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