Development of an AI-Driven Data Analytics Platform for Business Optimization

The client faces challenges in integrating and analyzing data from various sources, including CRM, ERP, and reports, leading to difficulties in deriving actionable insights for cost reduction and operational efficiency. Current data workflows are fragmented, resulting in suboptimal decision-making and higher operational costs.

A mid-sized enterprise utilizing multiple operational and customer data sources such as CRM, ERP, and reporting tools to optimize operations and reduce costs.

• Implement a unified data analytics platform to structure and analyze diverse data sources.
• Develop real-time and historical data visualization dashboards to support decision-making.
• Create an efficient data aggregation and retrieval interface for end-users.
• Achieve measurable operational cost reductions, targeting efficiency improvements.

• Integration of multiple data sources (CRM, ERP, reports) within a structured data environment.
• Interactive dashboards with historical and real-time data visualization capabilities.
• A centralized interface for data aggregation, querying, and retrieval.
• Support for scalable data processing and analysis pipelines.

• CRM systems to access customer data
• ERP systems for operational data
• Reporting tools for historical data analysis
• Real-time data feeds for live analytics

• Platform must support high-volume data ingestion and processing.
• Real-time data updates with minimal latency.
• Secure data handling compliant with industry standards.
• Scalable architecture to accommodate future data growth.

The implementation of the data analytics platform aims to reduce operational costs by approximately 13%, enhance decision-making with real-time insights, and streamline data workflows—resulting in improved business efficiency, reduced expenses, and better resource allocation.