Why Augmented Analytics?
Data plays a crucial role for organizations in staying ahead of the curve. Making sense out of data, deriving actionable insights that allow you to take faster and smarter decisions etc have been the key tenets for most organizations.
But as data got bigger and volumes became overwhelming, the traditional approach to data and analytics became increasingly insufficient. The primary reason for this is the manual dependency of these traditional tools-while exploring and preparing data, testing the models and finding certain patterns and even while sharing the results with the business.
Business and IT leaders realized that the manual approach leads to skewed results, because humans often come with perceptions and biases! Typically, data scientists tend to explore only a small percentage of the overall data, assuming that the rest is irrelevant or simply because there is way too much data to analyse! This brings down the possibility of deriving more relevant results.
Additionally, there is a huge skills gap when it comes to data scientists and experts, which also makes them very expensive and unaffordable for smaller businesses. That said, these experts still spend most of their precious time ‘preparing’ data, rather than doing actual analysis.
The Data Warehousing Institute found that 65% of respondents spend anywhere from 41 to 80% of their time on data preparation!
With augmented analytics, the various aspects of data analytics-preparation, insight discovery, insight sharing-are automated using machine learning and natural language generation. It improves overall speed and accuracy; more data can be analysed, and data biases can be reduced.
Besides, augmented analytics enables data scientists to focus on specialized problems, rather than doing simple mechanical things like labelling and cleaning their data. On the other hand, automation makes analytics accessible to business and operational users as well.
In the next two years, augmented analytics capabilities will be the “dominant driver of new purchases” of business intelligence software, Gartner predicts.