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Cloud-based BI solution for a food supply chain company

Client

A manufacturer of smart tray systems for transporting fresh produce

Industry

Food supply chain and logistics

Services

BI platform development, data architecture design, cloud migration, data pipeline automation, data governance

Tech stack

Microsoft Azure, Azure Blob Storage , Azure Synapse Analytics, Azure Data Factory, Microsoft SSIS, Power BI, Microsoft Master Data Services (MDS), Snowflake

Challenge

A company that manufactures reusable smart trays for fresh food logistics (such as meat, seafood, fruits, and vegetables) was experiencing operational inefficiencies that led to significant financial losses. Their legacy analytics systems did not provide real-time access to business-critical data, making it difficult for logistics and warehouse teams to respond quickly to delivery delays or perishable inventory risks. Products were often spoiled as a result of the outdated inventory information and the failure to meet the expiration thresholds. Additionally, the delays in the generation of business intelligence (BI) reports and their incomplete nature prevented supply chain companies from making rapid, data-driven decisions in the areas of finance, logistics, and production. In order to resolve these challenges, the organization required a centralized data platform that would function as a single source of truth and provide employees across departments with the most recent information.

Solution

To revamp the customer’s logistics and BI workflows, ITRex logistics software development company, designed and engineered a cloud-based Operational DataHub using Microsoft Azure services. The BI solution simplified data ingestion, processing, and reporting while laying the groundwork for future AI integration. We took on the following challenges:

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Centralizing data ingestion. The ITRex team integrated data from logistics, production, financial, and master data systems into Azure Blob Storage, ensuring unified, scalable access to a wide range of data sources.

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Automating ETL pipelines. To automate and orchestrate data extraction, transformation, and loading (ETL) processes, we implemented Azure Data Factory and Microsoft SSIS services, achieving near real-time delivery of cleansed, accurate data to downstream systems.

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Creating a single source of truth. Our data engineers organized and consolidated the ingested information in Azure Synapse Analytics, allowing the client's analytics and reporting teams to work with consistent, reliable data.

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Migrating from Microsoft SSAS models to Microsoft Power BI datasets. We transitioned the existing analytical models from on-premises SSAS (Tabular) to Power BI datasets. This enabled a unified, scalable, and self-service analytics experience directly within the Power BI platform.

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Implementing self-service business intelligence. The ITRex team leveraged Power BI to create intuitive and robust analytics dashboards. The solution allows employees from multiple departments to create and access real-time dashboards without requiring assistance from IT specialists or relying on centralized report generation.

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Establishing data governance. We assisted the customer in implementing a governance framework for secure, role-based access to data, which reduced security risks and promoted a data-driven culture throughout the organization.

Business Intelligence Solution for a Food Supply Chain Company

Business Intelligence Solution for a Food Supply Chain

Impact

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Employees in the logistics, warehousing, and finance departments gained access to live, reliable business data

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Automated analytics allowed the food supply chain company to track inventory state and optimize delivery schedules, reducing waste caused by goods’ expiration

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BI automation eliminated manual reporting delays and streamlined time to insights across the entire supply chain

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The cloud-native architecture effortlessly supports growing data volumes and disparate data sources without affecting the BI solution's performance

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The new platform is fully ready to support machine learning and predictive analytics, allowing the client to take the next step in operational optimization