Modern Data Architecture for Scalable Real-Time Business Insights

The organization faces fragmented data sources, manual data processing workflows, and infrastructure scalability issues, resulting in delayed insights, reactive decision-making, and difficulty in handling increasing data volumes as the business expands.

A large, rapidly growing enterprise in the business services sector seeking to optimize data operations, automate reporting, and enable real-time analytics for improved decision-making.

• Reduce manual data processing time by at least 80% to enable faster insights.
• Provide real-time access to key performance indicators through self-service dashboards.
• Integrate disparate data sources into a unified, accessible data ecosystem.
• Design a scalable, modular architecture that accommodates future data sources and reporting needs.
• Enhance operational efficiency and empower leadership with up-to-date, actionable intelligence.

• Migration of data operations to a cloud environment utilizing scalable platforms like Azure and Databricks.
• Development of custom ETL pipelines for seamless extraction, transformation, and loading of data from sources such as enterprise applications and spreadsheets.
• Creation of real-time, self-service dashboards for executive KPI monitoring and analysis.
• Design of a modular, easily extensible architecture to support additional data sources and advanced analytics functionalities.
• Implementation of data governance, security, and compliance measures.

• Enterprise data sources (e.g., Quickbase, Excel, other internal systems)
• Business intelligence tools for reporting
• Security and access management systems

• System scalability to handle increasing data volumes as the business grows
• High-performance data processing with minimal latency for real-time analytics
• Robust security and data privacy compliance
• High availability and fault tolerance

The implementation aims to reduce manual data processing by approximately 80%, enable instant, real-time access to operational metrics, unify data sources to provide a complete view of business performance, and future-proof the infrastructure for ongoing growth and evolving analytics needs.