Extensibility with StreamAnalytix - Real- time Streaming Analytics Platform

Extensibility

Keep full control and flexibility to add new functionality and interfaces as the technology ecosystem evolves

Use Extensions API for Custom Logic

With the Extensions API exposed by the platform, you can now write your own functionality in the language of your choice (Java, Scala, SQL, and Python), and make it available for all users across the platform.

Create Custom Data Operators

Connect to nearly any data source and data storage system with custom APIs.

Introduce custom data processing using various native Apache Spark and Apache Storm-based operators.

Create Custom Data Operators

Connect to nearly any data source and data storage system with custom APIs.

Introduce custom data processing using various native Apache Spark and Apache Storm-based operators.

Enables Custom Machine Learning

Build customized algorithms in a language of your choice (including Python and R).

Rapidly port predictive analytics and machine learning models built in SAS or R via PMML onto real-time data.

Well-Defined Extensions API Implementation

Each component or API extension has a well-defined API template that holds the business logic and lifecycle methods for implementation.

Well-Defined Extensions API Implementation

Each component or API extension has a well-defined API template that holds the business logic and lifecycle methods for implementation.

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Ten must-haves for a powerful enterprise data science solution

Data science solutions enable enterprises to explore their data, develop machine learning (ML) models, and operationalize them to drive business outcomes.

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blog Dec 07, 2020

Essentials for an enterprise data science solution

Data science solutions enable enterprises to explore their data, develop machine learning (ML) models, and operationalize them to drive business outcomes.

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