Real-time analytics projects usually begin with great excitement – crafting the minimum viable product (MVP) to prove the concept – but often lacking the Governance necessary to ensure success. 12-18 months later, Technical Debt has accrued steadily and begins to impact delivery timelines. In hindsight, it is often recognised that it takes more than IT know-how to correctly handle Engineering data.
Before I became a PI System Integrator, I spent many years as an end user, building spreadsheets and tools gathering real-time data to produce statistical summaries. Data from hundreds of sensors were constantly processed and combined to create a rich overview of asset production, allowing us to forecast those figures into the weeks and months ahead.
Summarising data in this manner is no mean feat – between the source instrument and final report, the data is normalised, corrected and converted. The Engineering Units applied at each stage are critical to ensuring the final figures are precisely correct – if you assign the wrong units to any figure at any point in the process, you’re in trouble. I knew the common conversion factors off by heart, and for completeness had them scrawled on a piece of paper above my desk.