Teradata Vantage™ 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 enables you to conduct analytics using languages such as SQL, Python, R, and third-party tools such as Dataiku and H2O, including any PMML-compliant tool.
- Vantage Native Data Preparation, Transformation, and Feature Engineering
- Analytics Database Analytic Functions: Teradata Vantage™ - Analytics Database Analytic Functions
- Vantage Analytics Library (VAL) for descriptive statistics, data transformation and reorganization, hypothesis testing, model building, and model scoring functions: Vantage Analytics Library User Guide
- Vantage Open Analytics: R and Python
- Script Table Operator and Exec R Table Operator: Teradata Vantage™ - SQL Operators and User-Defined Functions
- Script Table Operator Orange Book (log on required): R and Python Analytics with SCRIPT Table Operator Orange Book
- Vantage Open Analytics: Bring Your Own Model (BYOM): Teradata Vantage™ - Bring Your Own Model User Guide
- Predictive Model Markup Language (PMML) model scoring
- H2O Model Object Optimized (MOJO) model scoring
- Vantage Open Analytics Client Libraries
Vantage implements its native and VAL analytic capabilities as SQL functions, adding Python and R interfaces within the client libraries. These client libraries generate and perform the appropriate SQL syntax for the analytic function transparently. As a data scientist, use R and Python to benefit from the performance and scalability of Teradata Vantage.
With Vantage, you can run R and Python natively in the Analytics Database using table operators. The client libraries provide R and Python interfaces to transparently generate the required SQL syntax. 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 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.
Data Exploration, Data Cleaning, and Feature Engineering Functions
| Function | Reference |
|---|---|
| SQL Reference | |
Data Exploration Feature Engineering Data Preparation Analytics Database Analytic Functions (Path and Pattern) |
Teradata Vantage™ - Analytics Database Analytic Functions |
Descriptive Statistics Data Transformation Hypothesis Testing |
Vantage Analytics Library User Guide |
| Time Series Aggregate Functions | Teradata Vantage™ - Time Series Tables and Operations |
| Window Aggregates | Teradata Vantage™ - SQL Functions, Expressions, and Predicates |
| Python Reference | |
Data Preparation Analytics Database Analytic Functions (Path and Pattern) Descriptive Statistics Data Transformation Hypothesis Testing Time Series Aggregate Functions Window Aggregates |
Teradata® Package for Python Function Reference |
| R Reference | |
Data Preparation Analytics Database Analytic Functions (Path and Pattern) Descriptive Statistics Data Transformation Hypothesis Testing Time Series Aggregate Functions Window Aggregates |
Teradata® Package for R Function Reference |
Modeling Algorithms, Model Training, and Model Evaluation Functions
| Function | Reference |
|---|---|
| SQL Reference | |
| Vantage Analytics Library Algorithms | Vantage Analytics Library User Guide |
| R & Python Micromodeling | R and Python Analytics with SCRIPT Table Operator Orange Book Important: Log on required
|
| Python Reference | |
Vantage Analytics Library Algorithms R & Python Micromodeling |
Teradata® Package for Python Function Reference |
| R Reference | |
Vantage Analytics Library Algorithms R & Python Micromodeling |
Teradata® Package for R Function Reference |
Model Scoring, Model Monitoring, and Life Cycle Management Functions
| Function | Reference |
|---|---|
| SQL Reference | |
| Vantage Analytics Library Scoring | Vantage Analytics Library User Guide |
R and Python Model Scoring BYOM Scoring |
Teradata Vantage™ - Bring Your Own Model User Guide |
| Python Reference | |
Vantage Analytics Library Scoring R and Python Model Scoring BYOM Scoring |
Teradata® Package for Python Function Reference |
| R Reference | |
Vantage Analytics Library Scoring R and Python Model Scoring BYOM Scoring |
Teradata® Package for R Function Reference |