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.

Part 3 — The AI Bottleneck Nobody Is Talking About

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

Walking the floor at CES this year felt like stepping into a future that suddenly arrived all at once. Everywhere you turned, there were robots, intelligent machines, autonomous systems, and increasingly lifelike interfaces. But unlike past years, many of these technologies no longer felt like fragile demos or research experiments.

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

Customers turn to Viviota and to NI technology to better measure and analyze machine data from sensors. It turns out, sensor data does not always work well with traditional IT software, and there is a gap of software tools for this purpose.

The complexity of the electric power industry creates enormous opportunity for Fortune 500 companies and promising technology companies. Increased energy demands, capacity limitations, environmental constraints, varying load shapes, distributed generation and the deployment of new smart technologies all come into play.

The epic storm in February in our home state, Texas, exemplified the fagile nature of our electric grid and the catastrophic consequences of it failure. While new technologies will be developed to build a robust and resilient 21st Century grid, this new grid is still in its infancy and will take years, most likely decades, to reach that utopia of which we dream.

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