Fosfor Spectra is a comprehensive DataOps platform to build and manage complex, varied workloads via a low-code user interface with domain-specific features, to deliver purpose-built cloud native data transformation. Spectra is designed with intuitive drag-and-drop features for data orchestration, data pipeline development, and cloud & hybrid implementation. The platform delivers high processing performance on Data-in-Motion as well as on static data.

Key features:

1. Data-as-a-Product: Empowers decentralized, domain-oriented teams to build data pipelines and data products as required. Independently maintain and automatically version-control data products while ensuring strong governance, access management, and discovery of data across domains and applications.

2. Domain data pipeline: In-built capabilities for domain specific processing pertaining to different businesses. Creates batch and micro-batch data pipeline for real-time analytics by integrating messaging queues and avoiding loss of messages during failovers.

3. Purposeful processing: Connect data from over 50 pre-built native connectors, perform exploratory data analysis and use processed data on 3 party applications with ETL stores, quality stores and operational stores respectively.

4. Hybrid platform: Deploy on cloud or on-premises as per the organization’s requirements and preferences.

5. High performant: Implement dynamic execution with optimized ELpT pipelines, and a purpose-built dynamic execution framework.

6. Governance: Authentication and authorization features with user management, audit, and integrations with Git to ensure version control. Data lineage is maintained from source to target with related transformation information across applications and processes.

Who is it for?

· Spectra is developed to cater data integration, transformation and preparation challenges for data engineers, data scientist and data analyst

· Enterprises across the Industries having requirements to integrate & centralize the data in data lake, cloud warehouses.

· Enterprises looking for on cloud migration or on cloud data Ops.