The Big Data Transformation
Anytime I’ve seen data collection in the news over the past year, it’s been bad news regarding people’s online privacy or people starting to question certain business practices from tech companies. My fear is that people will associate these bad headlines with big data and therefore give it a bad name. The reality is that big data solves a lot of really complex problems and businesses should continue utilizing this tool (in an ethical manner) to gain efficiencies that might otherwise be impossible. If ever there was an industry that was ultra concerned with efficiency, it’s the energy industry.
Back in 2018, GE unveiled an engineering marvel that is their Digital Wind Farm. To be clear, this isn’t an ad for GE, rather a case study of how they have found a use for big data to gain efficiency. Sure the physical hardware here is super impressive, and makes you realize that we are living in the future, but what intrigues me here is how they are using software to analyse the condition of this wind farm.
The key to success for this wind farm lies in the ability to collect and deliver the right data, at the right velocity, and in the right quantities to a wide set of well-orchestrated analytics… — GE
There are four key features that comprise this digital solution. The first is the real time data that is collected and analyzed from each wind turbine. The second is being able to identify the problem by processing the data and quickly being able to identify any analytical anomalies that the data is exposing in hopes to correct the issue before it escalates. The third is deploying resources that are able to be equipped with the right information they need to quickly and properly attend to the fleet. The final component is that they are able to achieve results that verify the investment in big data. GE is able to enjoy an revenue increase, decreased costs, increased reliability, maximizing their investment by taking care of their assets, and decreased risk of failure. When you look at it through this light, why aren’t more industries using this technology to maximize their return on their investment
Optimizing Industrial Data Management and Operations
The cadence at which you need to be able to collect data from a wind turbine is what makes this case a perfect candidate for big data. According to GE, a turbine has a data frequency of about 100 tags every 40 milliseconds. This is so high because they need to be able to monitor and optimize this asset, they need to have data surrounding the current operations of the turbine. “The key to success for this wind farm lies in the ability to collect and deliver the right data, at the right velocity, and in the right quantities to a wide set of well-orchestrated analytics and provide insights at all levels in the operation. This requires a distributed computing fabric optimized for industrial big data in its many forms and in support of its many different uses. These requirements span the industrial world and are what drive the need for an industrial big data platform.” [1]
Other Industry Examples
Of course, energy isn’t the only field that can benefit from big data. There are several other fields that already are implementing these types of solution:
- Viz Explorer helps casinos use big data to make their operations more efficient and better for their customers.
- Hulu and Netflix use big data to analyze user tendencies, trends in consumptions, and more so that they can make their product even better. This analysis is worth a read if you’re more interested in how Hulu uses big data.
- Finance was probably the first adopters of big data. Hedge funds used big data and quantitative models to get a leg up on their competition. Now it’s almost standard practice.
- Healthcare has always consisted of a lot of data and by utilizing big data, it gives providers the ability to improve the quality of life. Particularly in the area of predictive analytics, this tech is invaluable.
As you can see, there are lots of applications for big data that are important for continuing to drive technology forward and make it more efficient.
