About the company

A leading health and security services firm providing multicultural health, security and logistics solutions from over 1,000 locations in 80+ countries.

Challenge

On its journey to further develop competitive products and services, the company wanted to design and build a modern data ingestion capability and revamp its legacy extract, transform and load (ETL), data storage and data consumption platforms. A primary goal was to deploy a decision engine by consolidating and streamlining content ingestion tools, processes and operations while helping to ensure data integrity and quality. Customer data was collated using multiple ingress protocols and ingested into a cloud-native enterprise data lake. The company was looking to design and integrate high-performance Application Programming Interfaces (APIs) for ingestion and consumption for analytics and visualization tools, third-party integrations, and web and mobile applications.

What we did

• Data governance model
• Data architecture
• Data catalog, data integration and data ingestion
• Enterprise data lake
• Amazon Web Services (AWS) data migration
• Cloud-managed services

Solution

The company was poised to embrace the public cloud for the first time with the help of Unisys Cloud, Applications & Infrastructure Solutions experts. AWS was the recommended data ingestion platform for its flexibility, reliability and scalability.

Our team categorized and created the solution architecture into three distinct parts:

• Ingress mechanism: Secure API, Secure File Transfer Protocol
• Data pipeline – Serverless ETL pipeline
• Data storage – Elastic search, cloud-native data lake and application database consumption

AWS Aurora with PostgreSQL 11 was the Relational Database Service for data storage. It provided innovative capabilities for non-functional requirements and enabled the company’s engineering teams to increase focus on pressing business problems:

• Designed and set up multiregion (U.S. Northeast and France) and multi-availability zone infrastructure to help ensure data security, availability and adherence to General Data Protection Regulation (GDPR) compliance
• Created a data governance framework for multiple environments and Identity & Access Management
• Designed and implemented an AWS Glue job to perform complex interactions with elastic search and insert, update and retrieve data into employees’ relational database management system
• Deployed AWS Data Wrangler within a Python Glue job using Structured Query Language (SQL) Alchemy for Object-Relational Mapping
• Aligned with business owners to redesign and migrate updated schema and reference data tables and refactored queries for application consumption from a legacy SQL server to Aurora PostgreSQL 11
• Implemented multiple secure ingress push/pull mechanisms that process numerous file formats, record structures and data types; ingested data becomes available for consumption with minimal tweaking

Result and outcomes

With the new architecture, the client embraced the AWS cloud, established multiregion cloud landing zones, and developed and productized a solution for employees and customers in less than four months:

Business benefits

• Established a cloud-native digital transformation foundation for the company
• Enhanced competitive advantage with innovative customer products and services via a next-generation data ingestion platform
• Enabled 24/7/365 global availability with region-specific compliance regulations and automatic backup

Technical benefits

• Enabled multiple parallel data ingestion and ingress protocols with high availability
• Successfully deployed a custom database for onboarding and authenticating customers through Okta to serve all applications
• Consolidated and streamlined content ingestion tools, processes and operations
• Gained the ability to design and integrate high-performance APIs for ingestion and consumption
• Improved geospatial support through PostgreSQL 11 and PostGIS