# Mature Data Platform Buildout

### Challenge

Rearc and Lazard partnered to build an end-to-end AWS native data engineering and data science platform. Various disparate data sources ranging from structured RDB tables to NLP processed data were piped to a data lake before ultimately being refined and loaded into data warehouses and data marts for BI consumption.

### Solution

- **Evaluate:** quickly and intimately learn the applications, environments, stakeholders, etc.
- **Plan:** create a detailed plan to make sure that we address all the key concerns, milestones, objectives, timelines, and more.
- **Execute:** deliver on what’s promised, lead by example, promote transparency, etc.
- **Retro:** use regular feedback loops to improve the quality and velocity of delivery.

### Outcome

- Customer learned how to use modern cloud-native technologies to address their data engineering needs.
- Acquired a modern data engineering platform with baked-in best practices.
- A single Data Platform Buildout project introduced the company to how we do DevOps, modern IaC, cleaner and faster Jenkins pipelines, concise and secure AWS best practices, and more.