Cloud-Native Analytics Platform for Managed Connectivity & Communications

Cloud-Native Analytics Platform for Managed Connectivity & Communications

Industry: Telecommunications

Overview

This case study outlines how MyntiQ Tech designed and implemented a cloud-native analytics platform on AWS for a managed connectivity and communications service provider. By unifying data from multiple operational systems into a centralized analytics layer, the organization gained fast, reliable business insights without impacting the performance of its core transactional databases.

Business Problem

The telecommunications provider faced critical data challenges:

  • Operations spanned multiple managed services (including SD-WAN, Voice, SIP, and UCaaS) which were supported by eight independent transactional systems.
  • Data was siloed across these systems, making cross-product performance and customer lifetime value reporting slow and manual.
  • Analytical queries were run directly on live production databases, impacting system performance and risking downtime.
  • The existing reporting infrastructure could not scale to support increasing data volumes or concurrent analytical queries.

How MyntiQ Tech Helped

MyntiQ Tech developed a high-performance analytics solution:

  • Cloud-Native Architecture: Designed a secure analytics framework on AWS optimized for scale, speed, and reliability.
  • Centralized Data Warehouse: Built a unified OLAP data warehouse using StarRocks to consolidate data from all eight operational systems into a unified model.
  • Data Orchestration: Implemented cloud-native pipelines with automated data reconciliation checks to ensure consistency across sources.
  • Decoupled Presentation Layer: Exposed analytics via a secure API, allowing operations, finance, and leadership teams to pull data into custom dashboards.

Business Outcomes Delivered

  • Delivered query performance that was significantly faster for complex, cross-product business analytics.
  • Eliminated analytical search loads on transactional systems, improving core database stability.
  • Created a single, consolidated view of customer accounts, service usages, and recurring revenue.
  • Supported data-driven decision-making across leadership, finance, and support departments.