Recognition ·
RapidMiner’s 2025 recognition
Based on G2 user reviews, in the Enterprise category, Winter 2025.
Machine Learning – RapidMiner
Machine learning to support business forecasting and decisions
With RapidMiner-based modelling, we help uncover patterns in your data and produce measurable forecasts for specific business questions.
01 /
Models built around business questions
We align forecasting or classification with the actual decision to be made. Such tasks include sales planning, customer retention, risk analysis and process optimisation.
02 /
Data preparation and model evaluation
We assess the quality and suitability of the data, then build and test the models. We evaluate the results against predefined metrics and the needs of business use.
03 /
Operational integration and monitoring
We connect the approved model to the decision-support process. Tracking its performance helps identify when changes in the data or the business environment call for a review.
Our approach
We start a machine learning project with the business question to be answered and an assessment of the available data. In a RapidMiner-based implementation, we pay particular attention to data preparation and to evaluating models in a comparable way. We plan the business rollout only once the test results and the limits of use are known.
How we work together
01Business goal and data assessment
We define what kind of forecast or decision support is needed. We assess the available data and how the model’s effectiveness will be measured.
02Data preparation and model building
We clean the data and structure it into a usable form. We build models suited to the task and compare them.
03Testing and business validation
We evaluate the models on separate test data and against business criteria. We document the accuracy limits and the conditions of use.
04Rollout and performance tracking
We integrate the approved model into the designated process. We track the results and define the schedule for later reviews.
Contact us
- Phone:
- +36 1 611 0462
- Email:
- info@blackbelt.hu