Enterprise Data Engineering & Integration
Connecting enterprise systems and data platforms through scalable pipelines, APIs, and hybrid integration architectures.
Modern organizations rely on data flowing between a wide range of systems, applications, and platforms. Integrating these environments reliably and efficiently is essential for supporting analytics, operational workflows, and modern data architectures.
Lyanix helps organizations design and implement scalable enterprise data integration architectures that connect legacy systems, modern applications, and enterprise data platforms.
Enterprise data challenges
Enterprise environments often include a mix of legacy systems, modern applications, and cloud platforms. Integrating these systems can create challenges such as siloed data across multiple platforms, specialized legacy integration requirements, and a combination of batch and real-time needs.
Hybrid data architectures
Most enterprise environments require both batch data pipelines and real-time integration. Lyanix designs architectures that support ETL and ELT data pipelines, real-time API integration, event-driven processing, and service-based integration across on-premise and cloud environments.
Batch Data Integration
Enterprise ETL pipelines, warehouse loading processes, scheduled transformations, and large-scale data movement across platforms.
Real-Time Integration
API-based integration, event-driven workflows, and service-based patterns that improve operational data accessibility.
Hybrid Integration
Architectures that combine batch and real-time integration to support complex enterprise data environments.
Platforms and technologies
Our team has experience across enterprise integration and ETL platforms including iWay, Talend, Azure Data Factory, and Informatica. These technologies are often used to move data between enterprise systems and modern data platforms such as Snowflake, SQL Server, DB2, and enterprise data lakes and warehouses.
Depending on the environment, Lyanix works within existing enterprise data models or supports the design and refinement of data warehouse and data lake architectures to ensure pipelines, analytics platforms, and AI systems operate efficiently.
Example integration architecture
Enterprise Systems
Mainframe, applications, databases, and operational systems.
Integration Layer
APIs, ETL pipelines, and integration platforms.
Enterprise Data Platform
Data warehouse, data lake, and governed data services.
Analytics & AI
Dashboards, reporting, advanced analytics, and machine learning.
Typical engagements
Examples of integration engagements Lyanix supports include enterprise integration architecture design, implementation of hybrid batch and real-time pipelines, modernization of legacy integration platforms, and integration of enterprise systems with modern data platforms.
Why organizations work with Lyanix
Enterprise data engineering experience
Over two decades delivering integration and data engineering initiatives across North America.
Legacy and modern platform expertise
Experience integrating legacy enterprise systems with modern cloud and analytics platforms.
Broad technology expertise
Hands-on experience across integration platforms, enterprise data technologies, and hybrid architectures.
Flexible engagement models
Support for focused initiatives, architecture design work, and larger integration implementations.
Explore connected service areas and modernization pathways.