What is Augmented Analytics vs. Automation?

Automation is a common feature in augmented analytics solutions, but it’s important to understand the difference between automating tasks, as many technologies do, vs. automating the decision-making that analytics informs. Automating data-driven decision-making takes away the need for human capability, whereas augmentation provides a methodology for underlying technology to guide users to uncover insights they might not see or discover otherwise.

Domain knowledge has always been important for analysis, but augmented analytics, fueled by AI and machine learning, make this skill set even more critical. There are often gaps where humans need to fill in the necessary context, and use the insight gained from analysis to help them make the best decision for the problem at hand. With augmented analytics, data analysts and business users can actually extract deeper, more granular insights in minutes - giving them a faster  time-to-insight compared to a traditional BI solution which requires a user to manually sift through data and insights. Diwo’s Decision Intelligence platform leverages augmented analytics and patented contextual intelligence to automate and augment a user’s decision-making process and deliver actionable recommendations in business context without the need for deep, technical skills or expertise in working with the data.