Enhancing Data Accuracy: How Much Can You Trust Your Data?

Our client, a leading logistics provider in the food and beverage sector, partnered with us to overhaul their data validation and reporting workflows. The result: faster insights, reduced manual labor, and complete confidence in reporting accuracy.
Supply Chain

About Customer

The client delivers comprehensive logistics solutions, focusing on the specialized needs of the food and beverage industry. Its integrated services ensure the secure and efficient movement of perishable goods across the supply chain, maintaining quality and compliance from origin to destination.

Project Summary

The project aimed to streamline and secure the client’s data reporting system through a fully automated, auditable data pipeline. Leveraging Azure cloud services, custom event processing, and real-time notifications, we built a solution that eliminated inconsistent metrics, reduced manual oversight, and delivered high-trust analytics. The outcome was a transparent, scalable, and reliable data infrastructure that empowered internal teams and strengthened customer

Challenge

Our customer used to spend excessive amounts of time double-checking datasets in their reporting to ensure accuracy. Often coming across incorrect metrics, resulting in the need for deep research and rebuilding new reports. As a result, our customer experienced drops in customer satisfaction ratings, and customers complains about unreliable reporting. 

Solution

  • We automated the data flow to Datawarehouse to check all raw data and compare it to the source.

  • The new data flow included checking data for consistency and veracity, and data cleansing. All business logic was crafted transparently by adding logs and audits to each step of the flow.  

  • The solution created an ongoing status report of the data for any timeframe (data snapshot) with a built-in notification system for deviations that allowed the customer to backtrace the execution process through every step. This allowed us to identify and fix discrepancies as soon as they arose. 

Technologies used

Azure Cloud
Azure Functions
Azure SQL server
Java React
Power BI

Results

Reliable data available on time
for users, management, and customers.
Informed business decisions
based on the real trustful state of things shown with the metrics.

Business Value

  • Optimized Data Operations:

    Automated data pipelines eliminated manual verification, reducing reporting time and increasing overall data workflow efficiency.

  • Enhanced Accuracy and Transparency:

    Built-in audits, logs, and data snapshots provided full traceability, improving trust in reporting and minimizing errors.

  • Proactive Issue Resolution:

    Real-time deviation alerts enabled immediate identification and resolution of data inconsistencies, ensuring timely and accurate insights.

  • Improved Decision-Making:

    Reliable and timely metrics empowered leadership to make informed business decisions with confidence.

  • Customer Trust and Satisfaction:

    Accurate reporting led to fewer complaints and improved client satisfaction, reinforcing the company’s reputation for reliability.

  • Scalability and Future Readiness:

    Cloud-based architecture and modular design allowed for seamless scaling to support business growth and evolving data needs.

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Lucy Levchenko Innovecs
Lucy Levchenko
Delivery Director
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