The Analytics Database Analytics Functions are a suite of scalable and distributed machine learning analytic functions to perform analytics on your dataset.
Using the Analytics Database Analytical Content
The content describes the advanced analytic functions used for feature engineering, training, scoring, evaluation, pattern recognition, and text analytics use cases. The database supports the use cases with a full dataset without compromising the end-to-end performance of an analytic workload.
Why Would I Use this Content?
You can use the content to understand which function to use for the following use cases:
- Data cleaning (which includes use cases related to handling outliers, handling missing values, and parsing data)
- Data exploration (which includes use cases related to descriptive statistics and statistical tests)
- Feature Engineering (which includes use cases related to feature engineering utilities and categorical and continuous variable transform)
- Model building (which includes use cases related to model training, model evaluation, and model scoring)
How Do I Use this Content?
You can use the content as follows:
- Select a function from the Overview section.
- Read the function description, syntax, syntax elements, and input and output sections for the selected function.
- Download the zip file and use the dataset setup file to create the datasets.
- Use the examples from the guide or SQL statements from the notepad and run the statements in the Teradata Studio or BTEQ environment.
How Do I Get Started?
Before using the functions, read the following sections:
- Read Usage Notes.
- Read the How to Read Syntax section.