Hitachi Vantara Pentaho+ Data Platform

Hitachi Vantara Pentaho+ Data Platform is a unified data integration and analytics solution engineered for enterprise-scale data fabric architectures. The platform combines ETL/ELT pipeline orchestration, self-service analytics, and data catalog capabilities within a single governed environment, enabling organizations to connect, harmonize, and activate data across heterogeneous on-premises, cloud, and hybrid sources. Its visual data flow designer supports both code-optional and code-first development paradigms, accommodating data engineers, analysts, and business users within shared collaborative workspaces.

The platform's enhanced data fabric layer provides metadata-driven lineage tracking, automated data quality scoring, and semantic layer management, allowing enterprises to establish trusted, reusable data products that persist across analytical workloads. Pentaho+ integrates natively with Hitachi Vantara's broader data operations ecosystem and supports connectivity to major cloud data warehouses including Snowflake, Google BigQuery, Amazon Redshift, and Azure Synapse Analytics, as well as operational databases, streaming sources via Apache Kafka, and object storage endpoints. The orchestration engine supports scheduling, event-driven triggers, and dependency-aware job execution at enterprise scale.

Pentaho+ is purpose-built for organizations managing complex, multi-domain data environments where governance, lineage, and analytical agility must coexist. Target workloads include enterprise data warehouse modernization, regulatory reporting pipelines, real-time operational analytics, and AI/ML feature engineering. The platform is available in both software-only deployment and as a managed cloud service, with role-based access control, audit logging, and encryption at rest and in transit supporting enterprise security and compliance requirements.

Ideal for

• Enterprise data warehouse modernization: orchestrating complex ETL/ELT pipelines to migrate and transform legacy data warehouse workloads onto modern cloud or hybrid platforms
• Regulatory and compliance reporting: building auditable, lineage-tracked data pipelines for financial, healthcare, or government reporting obligations with documented data provenance
• Real-time operational analytics: ingesting and processing streaming data from IoT sensors, transactional systems, or event queues via Kafka integration to support live dashboards and alerting
• Self-service analytics enablement: providing governed semantic layers and curated data catalogs that allow business analysts to explore and visualize data without direct database access
• AI and ML feature engineering: preparing, transforming, and versioning high-quality feature datasets for data science teams consuming outputs through notebooks or MLOps pipelines
• Multi-cloud data fabric implementation: unifying data access and governance across AWS, Azure, and Google Cloud environments to create a single logical data fabric without full data centralization

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.