Why engineering data preparation is the hidden ROI driver

Engineering data preparation is the systematic process of cleansing, structuring, enriching, and tagging raw test and sensor data so engineers can find, trust, and use it quickly for analytics and AI. Done well, it turns chaotic files and logs into a reusable asset that cuts time-to-insight from days to seconds and unlocks predictive models.

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Viviota and Rockfish Partner to Accelerate AI-Driven Engineering with Real and Synthetic Data

Over the next few weeks, I’ll be sharing a short series of observations from CES 2026 across three themes:

Engineering teams possess an underutilized goldmine in today’s fast-paced industrial landscape: their data. From sensor readings and vibration logs to video, sound, and test metadata, engineering data holds critical insights that can accelerate innovation, reduce costs, and safeguard operations against failure. Yet, a significant portion of engineering time is wasted merely searching for, organizing and wrangling data to make it usable.

Barry Hutt co-founder Viviota

Harvard Business Review[i] reported that cross-industry studies show, on average, less than half of an organization's structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or even used at all. 

This is post 2 in the series on 'The 7 Data Habits of Highly Effective Product Companies'. Tune in to our LIVE WEBINAR '7 Data Habits of Successful Product Companies' - MARCH 31, 11 a.m. CDT

Around the globe, in practically every sector, manufacturing facilities are undergoing a major transformation. Factory 4.0, Smart Factories, is becoming a reality. Digitization is changing the way we process materials and make products. Data and the intelligence it can provide is proving to be the key to completely reshaping manufacturing.