Enhanced data engineering and deployment
Improved deployment velocity and reliability
Improved operational efficiency
DevOps-enabled retail insights
The challenge
Enhancing DevOps practices for Retail Management Services (RMS)
A leading beverage company aimed to enhance its DevOps practices for its Retail Management Services (RMS) platform. They sought to improve existing data engineering and deployment strategies to address the evolving needs of their retail insights and analytics.
Key challenges
Need for better data/DevOps pipelines
Need for better AWS Redshift/RMS analytics
Need for better CI/CD, infrastructure management
Need for data catalog, consistent deploys
Scope for DevOps evaluation/upgrade
The solution
Scalable DevOps and data transformation
DevOps AI and Infrastructure
AI-powered DevOps
AWS IaC (Terraform)
Automated deploys
Data and CI/CD
Enhanced data engineering
Improved data quality
Federated CI/CD
DevOps and standards
Achieved DevOps maturity
Provided standard templates
Enable process standardization
The impact
Effective DevOps model development
Effective DevOps model development
Cost efficiency and scalability
Flexibility and increased deployment velocity
Improved security and error prevention
Consistency, reliability, and stability
Increased operational efficiency
Positive impact on data engineering capabilities
Higher efficiency in deployment processes
Improved data quality and reliability
Key strategies
Automated CI/CD pipelines
Seamless real-time adjustments
Client-centered robust infrastructure management
Looking ahead
Enhanced monitoring
Expanding functionality to include more detailed monitoring and alerting
Iterative product offerings
Enhancing DevOps practices for growing data engineering needs
Versatile data engineering
Supporting distinct data analysis goals with many data sources
