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core
features

Agile Data Engine combines features that are typically found in separate software products. Continuous data product delivery capability consists of five key feature areas. 

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data-model-tranformation

Data modeling and Transformations

Design the data products as logical entities and packages: data models and data load definitions such as transformations, business rules and dependencies.

  • Metadata-based data entity and transformation design and custom SQL transformations and rules.
  • Configurable entity (table, view) types  and templates for automating development and governance.
  • Searchable data model and data lineage visualizations for audit trail and impact analysis.
continuous-deployment

Continuous Deployment

Out-of-the box continuous delivery workflow with built-in CI/CD pipelines with automatic schema changes.

  • Generation of SQL DDL and DML scripts to be deployed to different environments.
  • Multi-database support, for generating SQL DDL and DML for different cloud database platforms.
  • Automatic schema change implementation without stopping data workflows.
workflow-orchestration

Workflow Orchestration

Load your data to the cloud database using metadata-based intelligent workflow generation, testing, orchestration and monitoring. Enabling business real-time data loading.

  • Generation of data workflows (directed acyclic graphs) based on model metadata.
  • Granular configuration of workflows based on entity level dependencies and schedules.
  • Dynamic load processing with concurrency control.
monitoring-testing

Monitoring & Testing

Workflow monitoring and timely data quality tests with an integration possibility to customer backend systems.

  • Monitoring and troubleshooting of dynamic data workflows (DAGs) and loads.
  • Customized metadata statistics reporting and visualization capabilities.
  • Data quality tests that can be executed as part of the workflow orchestration, and they can control the success of the workflows.
API-connectivity

API Connectivity

Easy-to-use metadata interfacing for operationalization and integration with existing systems and processes.

  • API connectivity to integrate ADE workflows with customer specific processes. 
  • Integration of metadata to data catalogs or other similar tools. 
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