AI & Data
Retail

Phase II: Microsoft Fabric Enterprise Implementation

Trility continued to help build a unified data model, enabling near real-time reporting. This empowered fast, reliable insights for sales trends, forecasts, and staffing at store and company levels while reducing redundancies by 50%, cutting report sizes by 99.9%, and improving access across the organization.

Problem Statement

Trility was hired back to continue optimizing this client’s fragmented and unreliable data ecosystem, which was difficult to maintain and prone to frequent issues. Data was pulled from multiple sources, leading to inconsistencies and a lack of trust in the insights generated.

The system’s inefficiencies extended to reporting, where large file sizes made generating and sharing reports time-consuming for end users. These challenges not only strained IT operations but also prevented the organization from confidently making data-driven decisions.

The client needed a streamlined, resilient solution that reduced redundancy, ensured data integrity, simplified access, and delivered fast, accurate, and trustworthy insights—all while being easier to maintain and scalable for future growth.

Solution Approach

To simplify and consolidate the client’s sprawling data ecosystem, we implemented a unified data model as the guiding framework, reducing redundancy and enhancing efficiency across multiple domains. By transitioning data from Synapse and Azure SQL to the Fabric stack, we reduced the total fields in critical areas without losing any insights:

  • Customer data was streamlined from 875 fields to 50.

  • Item data was reduced from 1,300 fields to 152.

  • Sales data was optimized from 767 fields to 86.

  • Inventory data was consolidated from 369 fields to 67.

Beyond restructuring the domains, we designed a reporting architecture for near real-time insights. Using medallion architecture, we layered the data pipeline to ensure accuracy, scalability, and speed. The smaller, more efficient system reduces infrastructure needs, management overhead, and costs while enhancing security and scalability. These improvements rebuilt trust in the client’s data and created a foundation for future growth and innovation.

Outcomes

By transforming and consolidating the data ecosystem, we rebuilt the client's trust in their data while enabling near real-time reporting capabilities. Now, no matter who in the company asks a question of the data, there will be just one place to get it and one answer.

Data is now accessible near real-time, providing faster, more reliable insights for year-over-year sales analysis, trend forecasting, and staffing optimization at both store and company levels. These improvements simplify maintenance, enhance performance, enable quicker reporting, and provide a scalable foundation for future growth, all while ensuring data integrity and security. Key metrics include:

  • Reduced report file size by 99.9%, enabling end-users to generate, share, and use reports more efficiently.

  • Consolidated five data sources and three credentials into a single source of truth, ensuring greater data security and streamlined access.

  • Optimized table relationships by 30%, reduced columns by 57%, and rows by 93%, cutting data management complexity and improving end-user performance.

Project Attributes

  • Reduced Technical Debt
  • Increased Uptime
  • Increased Scalability
  • Reusable Patterns
  • Increased Capabilities
  • Increased Security
  • Coaching
  • Documentation
  • Videos

Technologies Used

  • Microsoft Fabric
  • Azure
  • Microsoft Dynamics 365
  • Dynamics F&O