Product Development Forecasting Global Vehicle Sales on AWS cloud

Client Overview

A leading financial information, analytics, and ratings provider offers essential insights and data to businesses, governments, and investors, helping them make informed decisions in global financial and automotive markets. Their services include credit ratings, benchmarks, and risk assessments across finance, energy, transportation, and commodities sectors. The organization plays a crucial role in driving transparency, growth, and efficiency through diverse platforms in the global market.

Scope of work

The Automotive forecasting application for automotive vehicles enables analysts to predict vehicle sales volume across different geographic locations using historical data and market trends. It provides an intuitive interface for analysts to adjust sales forecasts for future years based on industry insights and economic factors. Analysts can compare multiple forecasting scenarios and apply adjustments dynamically to reflect market shifts. The application supports granular forecasting at country, and global levels for better decision-making. Overall, it empowers automotive companies to make data-driven, strategic business decisions.

Business Challenge

Scalability of Data Processing : Handling millions of data records efficiently while ensuring smooth performance for multiple users requires a scalable architecture.
Data Isolation and Multi-Tenancy: Since each user requires a separate dataset, implementing strict data isolation while maintaining efficient storage and retrieval mechanisms is a challenge.
Real-Time Data Slicing & Dicing: Users need the ability to filter, aggregate, and manipulate large datasets interactively.
Data Security & Access Control: Implementing robust access control to ensure users only access their own data is essential.
Cost Optimization for Storage & Compute: Storing and processing massive amounts of data can be expensive.
Concurrency & Performance Bottleneck: With multiple users performing high-volume queries and transformations, preventing performance degradation due to concurrency issues requires caching, indexing strategies, and load-balancing techniques.

JRD Solution

Scalable Data Processing Architecture: Successfully implemented an AWS-based scalable architecture to handle millions of data records efficiently, ensuring high-performance processing for multiple users.
Multi-Tenant Data Management: Implemented secure data isolation for each user using AWS services (S3, DynamoDB, AWS Batch, Redis Cache, Lambda) to ensure each user’s data remains separate and secure while allowing seamless access.
High-Concurrency Handling: Engineered a system capable of supporting multiple users performing complex queries simultaneously without performance degradation, utilizing caching strategies.
User-Friendly Data Visualization: Developed interactive and dynamic data visualization features using High charts
Separate workflow systems were established and orchestrated using AWS Step Functions, enabling smooth execution of batch jobs and nightly processes.
We worked closely with the client’s analysts and experts to develop a customized solution that aligns with both business and technical objectives. Our approach ensures compliance with global and industry standards, guaranteeing widespread acceptance.
Numerous microservices were developed to support the distributed architecture, enhancing flexibility and scalability using AWS Lambda and Batch.
The user interface (UI) was built using multiple Angular applications, seamlessly integrated into a unified portal for an optimal user experience.

Key Benefits

Optimized Data Query Performance: Implemented real-time data slicing and dicing capabilities using AWS Batch, Python, Polars, Lambda, and Elastic Cache enabling users to process large datasets with minimal latency.
Advanced Security & Compliance: Enforced strong IAM policies, data encryption, and VPC configurations to protect user data and comply with industry security standards.
Implemented a comprehensive AWS disaster recovery, high-availability strategy, and automated backups. Integrated AWS security best practices throughout the solution to uphold data protection and regulatory compliance.
Cost Management: We implemented a cost-effective serverless architecture using AWS to minimize computing expenses while ensuring high availability. Additionally, AWS Budgeting and Cost Management tools were leveraged to optimize resource utilization and control spending.
Implemented Comprehensive Monitoring & Logging for auditing and compliance requirements. Implemented continuous integration/deployment and implemented robust authorization and authentication mechanisms.