Modernizing Data Infrastructure for Operational Independence

Overview

Led a multi-phase migration and automation project to support a company’s transition away from their parent organization’s systems.

Challenge

The client’s operations were heavily dependent on a deprecated data source and legacy codebase. With the transition, they needed fast, scalable replacements for mission-critical workflows—including tank monitoring and operational reporting.

Solution

• Tank Balance Analysis: Shifted data inputs to Seeq PI Tags and rebuilt the process in Microsoft Fabric. Output is saved to both Excel and Lakehouse tables, feeding into a Power BI report that mirrors the original Excel format for a seamless end-user experience.
• Tank Temperature Forecasting: Developed a Fabric notebook that runs every 15 minutes, sends alerts when thresholds are exceeded, and logs data to Lakehouse tables.
• PowerApps Data Stream: Created a high-frequency Databricks notebook to load Seeq data into a Data Catalog used by PowerApps. Optimized performance by switching from SPy to Seeq API with multithreading, reducing latency from 120s to 10s.

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Key Benefits

Eliminated legacy system dependencies, halved processing times, and delivered user-friendly, scalable workflows integrated with Power BI and PowerApps.

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