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Enterprise Integration Services
Winjay Solutions’s Digital delivers expertise in solving integration problems for global business houses with its highly robust, stable, and scalable integration solutions, on-premises, and in the cloud which is powered by Agile and DevOps practices.
Provide secure custom API services for legacy and new enterprise applications to facilitate backend systems for mobile, desktop, and cloud applications; firmware/middleware, databases, and browsers.
Integrate third party APIs with applications including middle-ware, messaging queue, SSO implementation, AD integrations, elastic search, payment gateway etc. delivering enhanced performance and unified experience.
Automate and integrate applications from various environments through an Integration platform as a service (iPaaS) using cloud-based APIs. With iPaaS connected to microservices, we integrate the on-premises applications and data with cloud applications and data.
Deliver solutions to issues related with data quality, terminology, inconsistent structure, missing data, inability to match data from different systems. We access, interpret and transform data for successful integration, delivering a unified view of data from multiple data sources.
DevOps
- DevOps Consulting
- Implementation
- CI / CD Pipeline
- Containerization
- Infrastructure as a Code
Advantages of Enterprise Integration Services
Consulting & Advisory
Expertise in institutionalizing Data-Architecture strategy, Data Governance models, Business Process Re-engineering, and highly scalable systems implementation across the data architecture framework.
Implementation
Across the data consumption continuum – Data Ingestion, Data Preparation, Data Storage, Data Visualization, Data Mining, and Data Analytics
Support & Professional Services
Across the Enterprise Data Management and the entire Enterprise Data Maintenance lifecycle right from Data Ingestion to Data Mining and Data Analytics
Cloud, On-Premise & Hybrid
Various Data Deployment Models for highly agile and cost-efficient Data Consumption methods across the Big Data value chain