This post originally appeared on Forbes.
Many industries today are absorbing, developing and deploying cloud-based software designed specifically for their sectors. This holds true for my industry, construction. As CTO for a company building construction software, I have a unique perspective on big data -- both what it promises and what it's already delivering.
I’ve seen how the adoption of technological advances can change both the way things are done, and how often they are done correctly. I believe that big data -- and the promise of how it will be able to draw insights and trends from massive amounts of information -- is at the center of a coming revolution for business and everyday life.
Gathering Big Data From Big Numbers
Big data’s fire is fueled by numbers. The possibilities seem limitless, and yet we’ve only just begun to scratch the surface of the insights that can be drawn from these numbers. Big data’s enormous number sets are expressed in terms of terabytes and petabytes – trillions and quadrillions of bytes, respectively. This means lots of densely packed data from which to extract the correlations and patterns that inform strategic thinking.
Information is woven throughout the digital fabric of modern life. Our smartphones, our keystrokes, our wearables (data-collecting wellness devices that provide info about vital signs, posture, repetitive motion, etc) and even our televisions, kitchen appliances and thermostats are constantly at work collecting data. Information is collected every minute from numerous sources and sent into the global cloud. The economies of work and life can be rewritten if those massive, information-rich datasets could be properly harnessed and deployed to improve how we function.
Using This Data For Good
The construction industry increasingly uses cloud-based software that collects and uses data from projects around the world. This data ends up in project reports that affect everything from purchasing decisions to worker safety.
Construction is an inherently dangerous profession, with hundreds of work-related deaths, and many work-related injuries, per year. But by aggregating and studying the data, we might be able to discern patterns that suggest some level of predictability to the spate of injuries. We can start to ask questions like: Can certain types of injury be linked to specific types of construction projects, or to certain geographies or climatic conditions?
Big data could also help with urban and rural planning. Imagine using a network of opt-in mobile apps throughout a city to log population movement in ways that suggest pedestrian congestion solutions. Imagine collecting data regarding population movement and health, which could suggest ways to slow the spread of crowd-dependent seasonal infections such as the flu.
Urban planners could also combine big data with info-gathering city sensors to help create a Smart City with civic spaces back-engineered to accommodate the needs and habits of the population. The Institute of Electrical and Electronics Engineers (IEEE) has already put together a subgroup focused on Smart Cities, and Alphabet's Sidewalk Labs is working on technology-focused urban applications as well. The possibilities are nearly limitless.
Finding Clarity Through Big Data
When set to the task, big data can provide answers to many, many questions. Looking at the data can bring a high-level clarity that will help us predictively address root causes. For instance, construction sites are beginning to make use of wearable sensors that record worker movement. Aggregate these results over thousands of worker hours, and the emerging picture could potentially help experts design practices that alleviate the repetitive motion injuries that plague construction.
As a construction expert, I’m in the business of building. I see big data as an invaluable tool to help us innovate in construction, but also in industries far beyond my own. Big data can help us make decisions with an accuracy that we've never had before. When big data’s riches are used for the common good and for creating profitable practices, then we will have turned data into gold.