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AI Platform Enhancement for Data-Driven Insights
  1. case
  2. AI Platform Enhancement for Data-Driven Insights

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AI Platform Enhancement for Data-Driven Insights

fluxitsoft.com
Retail
Consumer products & services
eCommerce

Data Silos and Lack of Actionable Insights

Global Retail Corp struggles with fragmented data residing in disparate systems (POS, CRM, marketing platforms, supply chain). This makes it difficult to gain a holistic view of their business, identify key trends, and make data-driven decisions. Existing analytics efforts are limited by the inability to easily integrate and analyze data across these silos, resulting in missed opportunities for personalization and optimization.

About the Client

A large, multinational retail corporation with a significant online presence, seeking to leverage data for improved customer experience, personalized marketing, and optimized supply chain management.

Key Project Goals

  • Unify data from multiple sources into a cohesive knowledge graph.
  • Enable real-time, actionable insights for improved decision-making.
  • Enhance customer personalization and marketing effectiveness.
  • Optimize supply chain operations through data-driven forecasting and analysis.
  • Increase operational efficiency through automated processes.

System Functionality

  • Knowledge Graph Construction and Management
  • Data Integration from Multiple Sources (POS, CRM, Marketing, Supply Chain)
  • Advanced Analytics and Reporting (Predictive Modeling, Trend Analysis)
  • Real-time Data Processing and Insights
  • Data as a Service (Dremio Adapter) – self-service data access for business users
  • Google BigQuery Integration – scalable data warehousing and analysis.

Technology Stack

Node.js
Kubernetes
Dremio
Google BigQuery
Graph Database

External System Integrations

  • POS Systems (various vendors)
  • CRM Systems (Salesforce, Microsoft Dynamics)
  • Marketing Automation Platforms (Adobe Marketing Cloud, Marketo)
  • Supply Chain Management Systems (SAP, Oracle)
  • Cloud Storage (AWS S3, Azure Blob Storage)

Non-Functional Requirements

  • Scalability to handle large volumes of data
  • High Availability and Reliability
  • Robust Security and Data Governance
  • Performance and Low Latency for Real-time Analytics

Expected Business Value

By implementing this AI platform, Global Retail Corp expects to achieve significant improvements in customer satisfaction, marketing ROI, operational efficiency, and revenue growth. The ability to gain real-time insights from unified data will empower data-driven decision-making across the organization, leading to a competitive advantage in the retail market. Estimated ROI is 20% within 18 months through optimized marketing spend and improved supply chain efficiency.

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