Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and BI platforms. It also augments data scientists by automating many aspects of data science, machine learning, and AI model development, management, and deployment.
As the modern data stack evolves, Augmented Analytics levels up insights generation by incorporating AI and Machine Learning in traditional BI, which enables data consumers to make sense of their data and turn it into insights.Augmented analytics tools help to increase the speed to insight, and prioritize actionable insights that move the needle, as a result, business stakeholders can easily find answers to their business questions. Augmented analytics solutions can scale traditional analytical workflows by automating part of the data exploration process, and testing every factor and combination of factors in the dataset. Users don't have to worry about not knowing where to look in the data or rely on limited domain knowledge to generate insights, which also improves data-democratization across the organization.