TDSP is a framework that combines the best practices from CRISP-DM and Scrum, with a strong emphasis on team collaboration. It provides comprehensive open-source documentation and incorporates Agile concepts to support data science projects.
The OSEMN Framework is a structured process for data analysis and machine learning that helps data analysts to structure their work and ensure that the results are reliable and meaningful. The five stages of the framework are: Obtain, Scrub, Explore, Model, and iNterpret.
CRISP-DM is a structured approach to data mining projects that consists of six phases: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation, and Deployment.
SEMMA framework is a systematic approach for data mining and predictive modeling. It consists of five main stages: Sample, Explore, Modify, Model, and Assess.
Web and app analytics tool to help you review data, statistics and more, driving and helping you grow conversion, retention and user interactions.
