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