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Scalable Cloud-Based Analytics Platform for Media Industry Insights
  1. case
  2. Scalable Cloud-Based Analytics Platform for Media Industry Insights

Scalable Cloud-Based Analytics Platform for Media Industry Insights

yslingshot.com
Media

Challenges Faced by Media Analytics Platforms in Scaling Operations

A media analytics company is experiencing increasing demand for its online reporting system that provides media companies with insights into the most engaging stories. Their existing infrastructure is unable to support the growth in user volume and data processing needs, risking decreased performance, reliability issues, and difficulty in scaling to larger customers. They require a scalable, secure, and reliable platform to accommodate growing client needs without compromising on deployment speed or system quality.

About the Client

A mid-sized media company providing online news analytics and reporting tools to media organizations seeking deeper audience engagement insights.

Key Goals for Scaling and Enhancing the Analytics System

  • Migrate the existing analytics platform to a scalable cloud infrastructure to support increased user volume
  • Eliminate dependencies on static file systems by leveraging cloud-based storage solutions
  • Automate deployment processes to ensure faster, more reliable software releases
  • Implement security best practices to protect sensitive data and infrastructure
  • Consolidate multiple code repositories into a unified source control system to streamline development workflows
  • Modify underlying application code to support scalable architecture and improved performance

Core Functional System Requirements for Scalable Analytics Platform

  • Migration of the platform to a cloud infrastructure offering high availability and scalability
  • Integration with cloud storage solutions to replace static file system dependencies
  • Automated deployment pipeline enabling single-click releases
  • Load balancing and auto-scaling configured across multiple servers
  • Unified code repository management for streamlined development and deployment
  • Application modifications to ensure platform performance and scalability

Preferred Technologies and Architectural Approaches

Cloud services platform (e.g., AWS or equivalent cloud provider)
Relational databases optimized for scalability (e.g., MySQL in RDS or comparable)
Serverless components (e.g., cloud functions or lambdas) for automation
Version control systems supporting repository consolidation (e.g., GitLab, GitHub)

External System Integrations Needed

  • Cloud storage services for scalable file management
  • Monitoring and logging tools (e.g., CloudWatch or similar) for infrastructure oversight
  • Continuous integration and delivery pipelines for automated deployments

Non-Functional System Requirements and Performance Metrics

  • Support for at least 3x user volume compared to previous infrastructure
  • Rapid deployment capability with a single click for updates
  • System reliability with high redundancy and minimal downtime
  • Security adherence to best practices, safeguarding data and access

Projected Business Impact and System Performance Outcomes

The new cloud-based analytics platform is expected to handle at least three times the current user volume, deliver higher system reliability and redundancy, and enable rapid deployment cycles. These improvements will support business growth, improve user satisfaction, and ensure secure, scalable insights delivery to media clients, promoting continued expansion and operational efficiency.

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