Data Platforms & Analytics Engineering

Modern organizations generate large volumes of data across systems, but often lack the architecture to make that data usable, reliable, and actionable.

Triveni Global helps companies design, build, and modernize data platforms that support analytics, AI, and operational decision-making.

We work across the full data lifecycle from ingestion and transformation to analytics, reporting, and AI readiness.

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

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 Warehousing & Analytics

We design structured data systems and analytics platforms that allow organizations to query, visualize, and act on their data.

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

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

Keep this clean and grouped, not scattered:

Airflow

Data Pipelines & Orchestration

Mage

Data Pipelines & Orchestration

Snowflake

Data Platforms

Databricks

Data Platforms

PostgreSQL

Data Platforms

ClickHouse

Data Platforms

Kafka

Streaming & Search

Elasticsearch

Streaming & Search

Power BI

Analytics & BI

Metabase

Analytics & BI

Sigma

Analytics & BI

Redash

Analytics & BI

PostgreSQL

Databases

Neo4j

Databases

AWS

Cloud & Infrastructure

Azure

Cloud & Infrastructure

Kubernetes

Cloud & Infrastructure

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.

Business Value

Unified and reliable data across systems

Faster access to analytics and reporting

Improved decision-making with structured data

Readiness for AI and advanced use cases

Reduced operational dependency on manual processes

Scalable and future-ready data infrastructure

Interested in discussing a project?

Let's do something great together