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Product Overview

The architecture of Zementis for IBM z Systems is designed to leverage the capabilities of the z/OS platform for predictive analytics. The main system components include the Model Management Service, the Scoring Execution Engine, and the Data Access Layer. The Model Management Service is responsible for storing and managing PMML models.

The Scoring Execution Engine executes the models against input data. The Data Access Layer provides access to data stored on z/OS. These components communicate via REST APIs and internal messaging queues.

Data access is performed using standard z/OS data access methods. 509 certificates. It uses Role-Based Access Control (RBAC) to manage user permissions.

Competing products often require data to be moved off the mainframe for scoring, introducing latency and security concerns. Zementis avoids this by performing scoring directly on z/OS. The product supports integration with Apache Spark on z/OS for advanced analytics.

Configuration is managed through a web-based interface.

Frequently Asked Questions

What are the most common operations performed with Zementis for IBM z Systems?

Zementis for IBM z Systems allows users to deploy and execute predictive models described in PMML (Predictive Model Markup Language). Common operations include model deployment, scoring data against deployed models, retrieving model performance metrics, and managing model versions.

What configuration files or interfaces are used?

The product exposes REST APIs for model management and scoring. Configuration files are used to define data source connections and system parameters. A web-based interface is available for monitoring and administration.

How does Zementis for IBM z Systems integrate with other systems?

Zementis for IBM z Systems integrates with Apache Spark on z/OS. It leverages the z/OS platform for data access and processing. It can also integrate with other z/OS applications through its REST API.

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