We've looked at the ability of customer churn, propensity to develop customers and ideas of what makes the ideal customer. We are reaching out to try and predict from a database of what customers would be matching.
Senior Practice Manager - Head of SAP at KPI Partners
Real User
2020-01-07T06:27:00Z
Jan 7, 2020
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.
Data Science Platforms empower data analysts to develop, evaluate, and deploy analytical models efficiently. They integrate data exploration, visualization, and predictive modeling in one cohesive environment.These platforms serve as indispensable tools for data-driven decision-making, providing intuitive interfaces and scalable computing power. They enable seamless collaboration between data scientists and business stakeholders, allowing actionable insights to drive strategic initiatives...
We've looked at the ability of customer churn, propensity to develop customers and ideas of what makes the ideal customer. We are reaching out to try and predict from a database of what customers would be matching.
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.