Azure, AWS, Big Data rebuild (Finance)
Challenges
- Data silos in AWS, Azure and the Cloud
- No overarching model or enterprise understanding of data
- Big Data projects failing due to poor data quality
- Too many teams and vendors with little concrete output or results
Industry: Finance
North America and Europe
Solution
- Using WAR, provided Architecture guidance and best practices for AWS
- Review of data architecture and processes for Azure relevant Big data processes using Databricks and Azure nature services
- Code Deployment, Reviews and Collaborative Development in both AWS and Azure
- Knowledge Transfer
- Setting up a proper data architecture based on data types, data heat maps, data usage and use cases, velocity and storage best practices
Benefits
- Data now treated as an asset
- Reusable patterns now exist
- Canonical model being deployment
- Improved data quality and data lakes output
- Better BI and ML implementations