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dotData Enterprise
What dotData Enterprise is
dotData Enterprise automates feature engineering and machine learning through a no-code workflow for predictive analytics. It connects to data sources, cleans and transforms data, and supports exploratory analysis and customized transformations. Feature discovery spans multiple tables and numeric, categorical, time-series, text, and geospatial data. Built-in AutoML covers algorithm selection, hyperparameter search, missing-value imputation, and outlier cleansing; explainability features include feature explanations and blueprint diagrams. The product supports complex table relationships and datasets with billions of rows. Listed sources include Amazon Redshift, Google BigQuery, Snowflake, Azure Synapse, Oracle, Teradata, Microsoft SQL Server, CSV, and Tableau Hyper files. Models can be sent to dotData Ops for deployment, with predictions available through the GUI or APIs; API and JDBC connectors can deliver results to BI dashboards and business platforms. Deployment can use customer AWS or Azure infrastructure or managed dotData Cloud. It is paid, with pricing on request and no free plan.
Who it suits
It suits businesses seeking predictive models, including users without data-science knowledge. Its multiple data connectors and large-dataset support may also fit enterprise-scale workflows.
What it does well
- No-code workflow automates feature engineering and machine learning.
- Supports numeric, text, time-series, and geospatial data.
- Includes explainability features and blueprint diagrams.
- Supports datasets with billions of rows.
- Predictions can run through the GUI or APIs.
What to know first
- No free plan is listed.
- Deployment options listed are batch.
Limits
The listed Enterprise plan has pricing available on request and requires a demo request. Deployment is described as batch, and no free plan is listed.
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| dotData Enterprise | Enterprise pricing not listed; request a demo | On request |
As dotdata.com lists them, read 7 Oct 2026. The maker's own page has the final word.
Getting started
- Open the dotData Enterprise website
- Request a demo to discuss needs and use cases
- Choose private cloud on customer AWS or Azure infrastructure, or hosted dotData Cloud
- Connect supported data sources
- Build models in the visual workflow and deploy to dotData Ops
Verdict
dotData Enterprise combines data preparation, feature discovery, AutoML, and explainability in a visual workflow. Prospective customers need to request a demo and pricing details.
Questions
Does dotData Enterprise offer a free plan?
No. dotData Enterprise is a paid product with pricing available on request.
Which hosting options are available?
It can run in a private cloud on customer AWS or Azure infrastructure, or in the hosted dotData Cloud environment.
How can predictions be delivered?
Predictions can run through the graphical interface or APIs. API and JDBC connectors can send outcomes to BI dashboards and business platforms.
What data sources are supported?
Listed sources include Amazon Redshift, Google BigQuery, Snowflake, Azure Synapse, Oracle, Teradata, Microsoft SQL Server, CSV, and Tableau Hyper files.
Does it explain models?
Yes. dotData Enterprise provides explainable features and models, including feature explanations and blueprint diagrams.
Facts from dotData Enterprise's own pages
- Audience
- The product is presented for businesses seeking predictive models, including users without data-science knowledge, and for enterprise-scale data workflows. · dotdata.com, 7 Oct 2026
- AutoML
- Built-in AutoML includes machine-learning algorithms, hyperparameter search, missing-value imputation, and outlier cleansing. · dotdata.com, 7 Oct 2026
- BI connectivity
- The product page says its API and JDBC connectors can deliver outcomes to BI dashboards and business platforms. · dotdata.com, 7 Oct 2026
- Current version
- dotData announced Enterprise 4.1 in November 2025, including prediction-error drill-down analysis and one-click transfer of outputs to dotData Insight. · dotdata.com, 7 Oct 2026
- Data preparation
- It connects to data sources, cleanses and manipulates data, and supports exploratory analysis and customized transformations. · dotdata.com, 7 Oct 2026
- Deployment
- The product page describes private-cloud deployment on customer AWS or Azure infrastructure and a hosted, managed dotData Cloud environment. · dotdata.com, 7 Oct 2026
- Explainability
- The product provides explainable features and models, including feature explanations and blueprint diagrams. · dotdata.com, 7 Oct 2026
- Feature engineering
- It discovers features across multiple tables and supports numeric, categorical, time-series, text, and geospatial data. · dotdata.com, 7 Oct 2026
- Founded
- 2018 · dotdata.com, 28 Sept 2026
- Headquarters
- San Mateo, California, USA · dotdata.com, 28 Sept 2026
- Integrations
- Listed data sources include Amazon Redshift, Google BigQuery, Snowflake, Azure Synapse, Oracle, Teradata, Microsoft SQL Server, CSV, and Tableau Hyper files. · dotdata.com, 7 Oct 2026
- Model deployment
- Models can be deployed to dotData Ops with one click, and predictions can be run through the GUI or APIs. · dotdata.com, 7 Oct 2026
- Purpose
- dotData Enterprise automates feature engineering and machine learning to build predictive analytics models through a no-code workflow. · dotdata.com, 7 Oct 2026
- Scale
- The Enterprise page says it supports complex table relationships and datasets with billions of rows. · dotdata.com, 7 Oct 2026
- Security
- dotData reports completing a SOC 2 Type II audit for the fourth consecutive year, with the 2026 audit scope including generative AI integrations and self-managed deployments. · dotdata.com, 7 Oct 2026
- Support
- dotData offers tailored support and asks prospective customers to request a demo to discuss their needs and use cases. · dotdata.com, 7 Oct 2026
Where dotData Enterprise stands on Freedom251
- Low-Code Machine Learning Platforms Software#15 of 28
- AutoML Software#24 of 30