When a business wants to roll out advanced analytics to its business users, it must consider the average skill level and understanding of analytical techniques and ensure that the solution it chooses will support its project goals. One of the most important factors of business user analytics is user-friendly, simple analytics in an augmented analytics environment.
This type of environment provides support to achieve the right visualization, prepare the data in the correct way for analysis and choose the right analytical techniques. In this way, business users can leverage predictive analytics and produce results that are clear and easy to understand – all without asking the user to create complex searches or to understand the deep and broad details of analytical techniques.
The goal is to provide insight and help users make a decision without frustrating them or taking up a lot of their time! To do this, the augmented analytics solution uses machine learning, Auto ML, and natural language processing (NLP) to help the user collect and analyze data with the guided assistance of a ‘smart’ solution. Users don’t have to select data columns or choose analytical techniques like classification or clustering. All they have to do is select the dataset they want to analyze. The system will interpret the dataset, select important columns of data, analyze its type and variety and other parameters and then use intelligent machine learning to automatically apply the best algorithm and analytical technique and provide data insight.
The augmented analytics solution can apply correlation, classification, regression, or forecasting, or whichever technique is relevant, based upon the data the user wishes to analyze, and the results are displayed using visualization types that provide the best fit for the data, with data presented in simple natural language. So, business users do not have to be data scientists or spend a lot of time gathering, analyzing and trying to understand results!
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