dotData

Founded 2018

Discover hidden business drivers and automate feature engineering across complex enterprise datasets

Pricing model

Demo

You can use dotData to discover key statistical patterns and business drivers hidden across multi-table databases. It automatically analyzes relational, categorical, time-series, and text data to generate features for machine learning models. Business analysts can build predictive workflows without writing code, while data science teams can accelerate feature engineering pipelines. The system creates explainable scorecards for decision-makers and tracks model drift in production environments, tracing performance drops back to specific source data tables to keep predictions accurate across all enterprise applications.

What dotData does

Generate machine learning features from relational tablesDetect model and feature drift over timeCreate predictive scorecards for risk analysisIdentify root causes of business KPI changesTrain predictive models with automated machine learningLabel unstructured text data for enterprise modelsDeploy data and feature pipelines without engineering assistanceAutomated feature engineering across complex relational database tablesNo-code predictive model creation for business analystsSource data diagnosis for detecting feature and model driftHypothesis generation connecting statistical signals to business outcomesOne-click record scoring and explainable scorecard generationMulti-modal data exploration for numeric, time-series, and text sourcesSingle-tenant dedicated enterprise cloud deployment