Description

Problem:
Gaps in databases make analysis less reliable and prevent the proper use of machine learning. Incomplete records disrupt customer segmentation, distort forecasts, and reduce automation efficiency.

Our Solution:
We fill in missing values using a hybrid approach:

• Statistical methods (mean, median, mode).

• Machine learning algorithms that predict the most probable values.

• Business logic rules that draw context from similar records.

Value:

• Preserves dataset integrity and analytical quality.

• Enables accurate forecasting and predictive modeling.

• Delivers more complete and reliable customer records.

Service Format:
Clients upload their datasets online, we apply the chosen imputation methods, and return a complete version with missing values filled in — along with a full methodology report.