Case Study - AI-powered analytics platform that makes sense of big data
DataSphere Analytics is an AI and business intelligence solution that enables organizations to process big data and turn it into valuable insights. Hallederiz Labs built the foundation of the platform with data integration, scalable cloud architecture, and advanced analytics modules.
- Product
- DataSphere Analytics
- Year
- Services
- Data Engineering, Artificial Intelligence, Cloud Architecture
Overview
DataSphere Analytics needed a stronger analytics infrastructure to handle its rapidly growing data volume. Existing systems were fragmented, unscalable, and slow—negatively affecting both operational efficiency and decision-making processes.
At Hallederiz Labs, our goal was to develop a platform that provides scalable data processing, deep analytics powered by AI, and real-time insights. We designed a solution built on a modern data stack to achieve this.
Our Approach
- Strategy & Roadmap: Data sources were mapped, KPIs defined, and a clear, phased roadmap established.
- Data Integration: Streaming data from multiple sources was consolidated on Snowflake.
- Advanced Analytics: Databricks and AI models enabled trend analysis, predictive forecasting, and anomaly detection.
- Cloud & Performance: Multi-region cloud infrastructure delivered low latency, high availability, and automatic scalability.
- Visualization & Self-service BI: Interactive dashboards were developed, allowing users to create their own reports easily.
What We Did
- Data Integration
- Snowflake
- Databricks
- AI Models
- Self-service BI
Hallederiz Labs modernized our data stack and accelerated our decision-making processes. We now manage our operations through measurable data and have a solid infrastructure that will carry our business into the future.
CTO, DataSphere Analytics
Results
- Faster data processing
- 2x
- Increase in analytics report usage
- +47%
- Reduction in operational reporting time
- -35%
- Data access continuity
- 99.95%
Technical Achievements
- Data Consolidation: Data streams from fragmented sources were unified in one central hub.
- AI-driven Analytics: Predictive models strengthened strategic decision-making processes.
- Cloud Architecture: Delivered high availability, low latency, and automatic scalability.
- Self-service BI: Users can now create their own reports without IT dependency.
Value Proposition
With the support of Hallederiz Labs, DataSphere Analytics transformed big data into measurable, predictable, and sustainable business intelligence. Today, the platform continues to grow on an AI-driven, cloud-based, and future-ready architecture.