dotData Enterprise: No-Code Insights & Data Science

Automate Data Discovery & Predictive Analytics

dotData Enterprise is an enterprise-grade platform designed to automate the entire workflow of advanced analytics. No-Code Automated Feature Engineering and Automated Machine Learning help you automate the process of discovering insights from your data and building Predictive Analytics models in days instead of months..

Deployed to Suit Your Needs

dotData Enterprise can be deployed to suit your individual business needs. Choose from private-cloud deployments on your AWS or Azure infrastructure, or get started quickly and easily by selecting our dotData Cloud environment, fully hosted and managed by dotData.

“Feature engineering is powerful and scalable, even across tens of tables with billions of rows.”

Profile data with dotData Enterprise
Step 1

Load your enterprise data

Connect to your data lake or data warehouse and leverage the full power of your enterprise relational data:

  • Load data from modern cloud data marts (including Amazon Redshift, Google Big Query, Snowflake, MS Azure Synapse),  traditional data warehouses (Oracle, Teradata, and MS SQL Server), and flat data sources (CSV files,  Tableau Hyper files, etc.) 
  • Extract or infer metadata information like data schema and entity relations directly from data sources. Normalize metadata from different sources
  • Visualize data with billions of records and hundreds of columns, assess data quality, perform exploratory data analysis, and apply customized data transformations.
Provide source and target for ML
Step 2

Provide Your Target & Source

Select your target variable and the source tables you will use to build features, then hit run, and dotData will do the heavy lifting in record time.

  • Resolve data quality issues like illegal values, outliers, data canonicalization, missing values, target label mapping and more.
  • Explore millions of feature hypotheses – including numeric, categorical, time-series, text, and even geospatial data.
  • Minimize domain bias with automated recommendations on features with the most predictive power. 
  • Build state-of-the-art ML models with gradient boosting, neural networks, ensemble models, decision trees, logistic regressions, and more.
  • Fine-tune ML model parameters and select the best-performing ones.
Step 3

Discover Transparent & Explainable Features & Insights

Discover and evaluate data insights and features with minimal effort

  • Understand each feature’s business value and construction via an easy-to-understand auto-generated explanation and feature blueprint diagram.
  • Select your preferred features based on various feature metrics like correlation, feature-wise AUC, permutation importance, feature locality, popularity, and more.
  • Perform feature segmentation analysis and discover the deep relationship between features or between the features and your target variable.
Auto Select the right ML Model
Step 4

Select The Right Predictive Model

Take advantage of ML auto-pilot to identify the best ML model most suited to build predictive models for your business

  • Use charts and a model leaderboard to analyze trade-offs between ML models to find the right one.
  • Leverage model recommendation to automatically compare model accuracy, robustness, complexity, and interpretability to help you get to the best model – easily. 
  • Visualize each model with different techniques like confusion matrix, ROC curve, lift chart, error histogram, etc.
dotData MLOps
Step 5

Deploy Your Models & Operationalize Predictions

Make deploying and monitoring your predictive models a snap with integrated MLOps capabilities.

  • Schedule predictions with near zero effort by deploying a model from dotData Enterprise to dotData Ops with a single click.
  • Use dotData’s API and JDBC connectors to consume outcomes in your BI dashboards and business platforms.
  • Run predictions using the best models via GUI or APIs.

You, AWS & Azure

Deploy dotData Enterprise behind your firewall or on your private cloud instance – whether on AWS or MS Azure, the choice is up to you.

Hosted by dotData

Get started quickly by leveraging dotData’s cloud-based instance of dotData Enterprise fully hosted and managed by dotData on AWS.

Justin Shoolery - dotData Client

Payment processor used dotData to recover $96M per year by implementing an ML-powered smart dunning process. Read how they did it.

Justin Shoolery
Director of Data Science & Analytics,

Ready for Predictive Analytics?

Book a 37-minute meeting with our solution specialists to see if predictive analytics – and dotData Enterprise – are right for your organization.