Teradata Vantage Analytics using SQL, Teradata Python or R - Teradata Vantageā„¢ Analytics Capabilities - Teradata Package for Python - Teradata Package for R - Teradata Vantage

Teradata Package for Python
Teradata Package for R
Teradata Vantage
Release Number
May 2022
English (United States)
Last Update
Product Category
Teradata Vantage

Teradata Vantage Analytics Capabilities

Teradata Vantage™ is a data and analytics platform that offers a wide range of features for data preparation, feature engineering, hypothesis testing, analytic modeling and scoring. It accelerates analytic workflows by providing a highly performant, scalable, enterprise data platform that performs production-advanced analytics with little to no data movement to and from other platforms. Teradata Vantage offers the best-of-breed choices and the ability to conduct analytics using tools and languages preferred by analytics professions such as SQL, Python, R and third-party tools Dataiku, H2O, including any PMML-compliant tool.

Teradata Vantage has the following analytic features and functions:

Vantage implements its native and VAL analytic capabilities as SQL functions. Then, adds Python and R interfaces on top of that within the client libraries. These client libraries are generating and performing the appropriate SQL syntax for the analytic function transparently to the end-user. Data scientists are using R and Python and benefiting from the performance and scalability provided by Teradata Vantage.

Vantage allows data scientists to run R and Python natively in the SQL Engine using table operators. The client libraries provide R and Python interfaces to generate the SQL syntax required transparently to the end user. If you have already selected a different analytic platform, the client libraries provide standard R and Python methods of exporting and loading data in parallel, not serially. Once your modeling is done in the other platform, PMML and H2O MOJO can be used to score the entire database back in the Vantage platform using SQL or the interfaces from the R and Python libraries.

Everything Vantage does from an analytic perspective can be accomplished in SQL, R or Python.

Modeling Algorithms, Model Training, and Model Evaluation Functions

Type of Function SQL Reference Python Reference R Reference
Vantage Analytic Library Algorithms SQL: Vantage Analytic Library Algorithms Python: Vantage Analytic Library Algorithms R: Vantage Analytic Library Algorithms
R & Python Micromodeling SQL: R & Python Micromodeling

Log on required

Python: R and Python Micromodeling R: R and Python Micromodeling

Model Scoring, Model Monitoring, and Life Cycle Management Functions

Machine Learning Engine

The Machine Learning and Graph Engines (ML/G) provide extensive analytic capabilities. The Teradata Vantage™ - Machine Learning Engine Analytic Function Reference provides syntax and examples for all its functions. The table below gives links to the various sections.

Teradata is leveraging the Analytics Database for Advanced Analytics Functions, and is reducing reliance on Analytics Nodes. The Analytics Nodes reached end-of-sale in December 2021. Analytics Nodes is supported until 2025.
Type of Function SQL Teradata Package for Python Teradata Package for R
Statistical Analysis Statistical Analysis Teradata Package for Python Function Reference Teradata Package for R Function Reference
Path and Pattern Analysis Path and Pattern Analysis
Data Preparation and Transformation Data Preparation and Transformation
Cluster Analysis Cluster Analysis
Time Series Analysis Time Series Analysis
Predictive Modeling Predictive Modeling
Text Analysis Text Analysis
Graph Analysis Graph Analysis
Association and Recommendations Association and Recommendations