How we Modernized Analytics Performance with an AWS-Native Reporting Framework
A digital services provider modernized its analytics with an AWS-native, serverless reporting framework — proving faster queries, lower production load, and self-service BI through a proof of concept.
At a Glance
Our client, a rapidly evolving digital services provider, needed to overcome performance bottlenecks and limited reporting capabilities in its existing analytics environment. Their PostgreSQL setup on GCP struggled to deliver fast, reliable insights due to architectural constraints, slow query execution, and limited visualization options. To strengthen decision-making and support future modernization initiatives, the organization launched a proof of concept (POC) focused on evaluating AWS-native analytics tools.
Challenge
Improving analytics speed, scalability, and user accessibility
The existing reporting environment faced frequent slowdowns, with analytical workloads competing against production systems and impacting performance. Teams lacked intuitive dashboards, struggled with long query times, and had limited ability to generate insights independently. These constraints reduced visibility across business functions and hindered the organization's ability to scale analytics efficiently.
The goal was clear: design and validate a modern, cloud-native analytics approach that decouples workloads from production systems, improves performance, and introduces self-service BI, including natural-language querying to empower non-technical users.
Solution
AWS-native analytics architecture built for speed and self-service
Our team delivered an end-to-end POC that demonstrated the performance and usability of an AWS-driven analytics stack.
- Modernized Analytics Architecture on AWS: Implemented a serverless environment using Amazon S3 for storage, Athena/Redshift for scalable querying, and QuickSight for fast, interactive visualizations.
- Enabled Dashboards and Natural-Language Insights: Built QuickSight dashboards and piloted QuickSight Q, allowing users to access insights through both visual reports and plain-English questions.
- Decoupled Analytics from Production Systems: Shifted analytical workloads off transactional databases, improving reliability, reducing contention, and enabling faster, uninterrupted queries.
Benefits
Faster insights, wider accessibility, and a clear modernization roadmap
The POC delivered measurable value across the client's analytics landscape:
- Significant Performance Improvements: Analytical and ad hoc queries ran considerably faster, reducing wait times and enabling quicker decision cycles across operational and reporting teams.
- Expanded Data Access Across the Organization: Business users gained the ability to explore data independently without SQL expertise or engineering support.
- Defined Pathway for Scalable Modernization: The initiative provided a validated blueprint for adopting a data lake architecture, natural language BI at scale, and future AI-enabled analytics powered by AWS.
Ready to modernize your analytics environment for speed, scale, and smarter insights?
zeb partners with organizations to transform legacy reporting environments into modern, cloud-native analytics ecosystems. From serverless architectures to natural-language BI and AI-driven intelligence, we help teams achieve faster insights, reduce operational load, and build a future-ready data foundation.
Let's elevate your analytics into a high-performance, insight-driven platform.
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