Augmented analytics is the use of technologies such as artificial intelligence (AI) and machine learning (ML) to transform how analytics can be built, consumed and shared. Originally defined by global advisory firm Gartner, using augmented analytics as part of your data analytics life cycle – data preparation, data discovery, insight generation and insight explanation – is done to not only help everyone better explore, analyze, understand and act on data, but to also transform, democratize and automate the use of data for all types of users. This has created a new designation, the augmented consumer.