Predictive modeling traditionally was the province of the data scientist and the analyst. A key trend, however, is the democratization of these tools. Modern platforms are increasingly user-friendly, offering automated workflows, pre-built models, and visual interfaces. Business users can leverage predictive analytics without requiring extensive coding skills.
Following are six of the best tools, according to various needs and levels of proficiency
Altair AI Studio: Altair AI Studio is an all-inclusive platform that provides a full suite for , text mining, and predictive modeling. Its notebooks make development easier for beginners, as well as experts. Altair performs many functions from preparing your data and generating models automatically to managing the deployment of a model.
H2O Driverless AI: This relatively new player is the leader in democratizing AI development and for experts and citizen data scientists. It boasts impressive capabilities in automated feature engineering, model selection, and parameter tuning, and natural language processing. It is exemplary in its focus on explainability, hence, it offers tools for understanding the decisions of models.
IBM Watson Studio: IBM Watson Studio is the market-leading platform for descriptive, diagnostic, predictive, and all in one place. It addresses the needs of both data scientists and business users by offering collaboration features that make the predictive analytics workflow much easier.
Microsoft Azure Machine Learning: Microsoft supplements its extremely popular analytics tools, namely Power BI and Excel, with Azure Machine Learning. Full-suite solution supporting complete predictive analytics lifecycle from data management to deployment, it appeals to a variety of user types. It offers integration with application development tools, thus enabling seamless integration of predictive capabilities into workflows.
SAP Predictive Analytics: This is a perfect solution for those organizations that have an extensive SAP deployment in place. It is the best solution to build predictive models for logistics, supply chain, and inventory management. Advanced users and business users have separate interfaces. Hence, SAP Predictive Analytics further simplifies data aggregation, modeling, and analysis.
SAS: Although the market leader in many analytics tools, including predictive modeling, having recently renovated its offerings with data science and machine learning workflows, augmented workflows, and simplified deployment, SAS has hundreds of tools across different domains. It enjoys very good relationships with cloud providers and is hence accessible across diverse workflows.
