As data scientists, we have to deal with bad formatting data sets with missing or wrong values, and many other problems that hamper our progress. Some studies, such as the Cleaning Big Data: Most Time-Consuming, Least Enjoyable Data Science Task, Survey Says, found that data scientists spend 60% of their time on cleaning and organizing data.
Once this process is completed, data analysis phase is performed. In this task, values, histograms, variables distribution, and correlations between them are studied. Most of the time, modeling phase involves repetitive analysis tasks, such as selecting the best algorithm by using automated procedures (for example, GridSearchCV in scikit-learn), or features selection process applying different predefined techniques.
In the end, all Data Analytics projects are very similar regarding methodology and techniques applied.
ADAM (Automated Discovery and Analysis Machine) system is developed in order to optimize our time and focus more on intellectual labors and techniques to solve the specific problem. ADAM is a framework that helps us to perform an automated analysis of the data set by applying Data Science techniques.