Data Platforms & Analytics Engineering
Triveni provides data platform and analytics engineering services to help businesses build scalable data architectures, improve reporting, and enable analytics and AI-driven decision-making.
Data Engineering & Pipeline
We build scalable data pipelines that collect, process, and structure data from multiple sources for downstream analytics and applications.
What We Do
- Multi-source data ingestion (APIs, CSV, Excel, enterprise systems)
- ETL / ELT pipeline development
- Real-time and batch data processing
- Data normalization and enrichment
- Pipeline orchestration and monitoring
Where It Applies
- Manufacturing data integration (MPN, BOM, supplier data)
- Healthcare data pipelines (claims, eligibility, pharmacy)
- SaaS platform data processing
- Event-driven systems using streaming
Data Warehousing & Analytics
We design structured data systems and analytics platforms that allow organizations to query, visualize, and act on their data.
What We Do
- Data warehouse architecture design
- Structured data modeling
- Analytics and BI platforms
- Dashboard and reporting systems
- Query optimization
Typical Outcomes
- Centralized reporting platforms
- Operational dashboards
- Financial and performance analytics
- SaaS product analytics
Data Modernization & Cloud Platforms
We help organizations transform legacy and fragmented data systems into scalable, cloud-native data platforms.
What We Do
- Migration from Excel / CSV / legacy systems
- Data architecture redesign
- Cloud data platform implementation
- Performance and scalability optimization
- Enabling AI-ready data ecosystems
Typical Outcomes
- Unified data platforms
- Modern analytics infrastructure
- Reduced dependency on manual processes
- Improved data reliability
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Advanced Data Use Cases (Differentiator Section)
Advanced Data & AI-Ready Systems
Beyond traditional data platforms, we build advanced data systems that support intelligent applications, real-time processing, and AI-driven use cases.
- Large-scale data normalization and similarity matching (MPN / parts)
- Graph-based data modeling (Neo4j)
- Search and indexing systems (Elasticsearch)
- Real-time data streaming platforms (Kafka)
- AI-ready data pipelines for LLM and RAG systems
Technology Capabilities
Airflow
Mage
Snowflake
Databricks
PostgreSQL
ClickHouse
Kafka
Elasticsearch
Power BI
Metabase
Sigma
Redash
Neo4j
AWS
Azure
Kubernetes
Selected Use Cases
Manufacturing Data Platform
Processed millions of MPN records across OEMs and contract manufacturers to build normalized datasets and enable accurate alternative part matching.
Healthcare Data & Analytics
Built ETL pipelines and analytics systems for eligibility, claims, pharmacy, and financial data to support reporting and operational workflows.
Ideal Clients
We partner with forward-thinking organizations that demand engineering excellence and architectural integrity.
SaaS Companies Building Data-Driven Products
Manufacturing / EMS Companies with Complex Datasets
Healthcare Organizations Handling Operational Data
Enterprises Modernizing Legacy Data Systems