KPI Dashboard

Overview

The KPI Dashboard was developed to give operational teams and management real-time visibility into production data, replacing scattered reports and inconsistent Excel workflows. The goal was to create a unified, role-based interface that made critical metrics accessible, timely, and actionable.

Responsibilities

I was responsible for the complete architecture and implementation of the system. Based on research into big data patterns, I designed a customized Lambda architecture to support robust data ingestion, transformation, and aggregation. This allowed us to process large volumes of data with multiple levels of time-based granularity (e.g. daily, weekly, monthly).

Contributions

• Designed a modified Lambda architecture for robust, scalable, and efficient data processing

• Implemented data aggregation across different time granularities (e.g. daily & monthly)

• Developed business logic using JavaScript Business Objects with scheduled batch processing

• Transformed external data formats via Microsoft Graph API (REST) and SAP connectors

• Designed and extended a SQL database referencing existing production data

• Designed and connected performant APIs for KPI aggregation

Challenges

The biggest challenge was designing a scalable data processing architecture that could reliably handle semi-large volumes of production data across varying time granularities. Integrating external systems like Microsoft Graph and SAP introduced complexity in both data consistency and transformation logic.

Ensuring smooth communication between the data layer, APIs, and the role-based dashboard demanded deep technical alignment across all parts of the system.

Impact

The dashboard enabled teams to access real-time production insights tailored to their roles, improving decision-making on the shopfloor and in management.

By streamlining data flows and reducing manual reporting, it significantly increased transparency, reduced errors, and established a scalable foundation for future analytics features.