It’s no secret that big data is getting…well, bigger – at an astonishing rate.
90% of the world’s data has been generated in the past two years alone (source: Domo). And sources estimate that the size of the digital universe is doubling at least every two years.
It’s worth noting that while human-generated data (e.g., data from everyday activities such as phone calls and social media posts) is growing much faster than traditional business data, data generated by machines is growing exponentially faster, at 50x the growth rate.
What’s driving this explosion in machine data, and what are some of the ways in which it might transform the world within the next few years?
Machine Data and the IoT
Most traditional business applications originated at a time when data was comparatively scarce and data storage relatively expensive. Crucial business functions like finance, marketing, and supply chain management were conducted in the rearview mirror, powered by historical reporting – for example, a report of last month’s transactions. A small number of IT systems would maintain detailed system logs, primarily in cases of security incidents.
But with the decline in the cost of data storage, an increasing number of sensors, devices, and applications are tracking and writing everything they do – producing a treasure trove of data.
Simply put, the category of machine data covers all kinds of data generated by pieces of technology (servers, industrial equipment, and mobile devices, for example) as they record the world around them and their own operations. Machine data is the “digital exhaust” created by the operation of these systems and applications: everything from server logs to records of machine temperatures.
The list goes on. Sensors. Traffic lights, Elevators. Routers. Exercise equipment. Medical devices. Surveillance cameras. Firewalls. Assembly line tools. Each and every one of these churning out billions of data points regularly on their operations. The computing abilities embedded in day-to-day objects and rise of machine-to-machine communications has fueled the growth of the Internet of Things (source: Wired).
Some industry experts have proposed a classification of different types of machine data, including sensor data (e.g., videos of a street corner), calculations and predictions, automation records, and metadata. However many types there are, though, one thing is clear: machine data is abundant and complex, and is only poised for further growth over the coming years.
The Machine Data-Powered Revolution
The availability of massive amounts of machine-generated data in real-time has fundamentally changed the way that businesses across industries approach decision-making. Some of the areas in which businesses have seen the biggest transformations include:
- IT performance and security. Granular system logs have turbo-charged network traffic and virtual machine monitoring, allocation of computing resources, and identification of network intrusions, (source: ComputerWeekly.com).
- Business intelligence. Key applications include demand forecasting based on store traffic (from mobile beacons), and predicting the right ad experience to deliver to users in different geographic areas or on different device types. Furthermore, data doesn’t have to intuitively correlate to the prediction subject – a Japanese real-estate company, for example, was able to create a predictive model for lease renewals based on machine data from their elevators (source: CITO Research)
- Manufacturing. The ability to capture detailed information on the operation of automation and processes – through the use, for example, of a digital twin – has fueled preventative maintenance and just-in-time ordering of parts used in industrial manufacturing, leading to significant cost savings and efficiencies.
Of course, the way that most consumers experience the benefits of machine data is through a network of “smart” devices powered by the IoT – thermostats that start heating the house when a resident is on her way home, or exercise equipment that automatically adjusts based on a user’s digital medical records and biometrics.
But the story doesn’t end with simply generating and gathering machine data. For businesses, getting value from machine data requires the ability to teleport that data from countless sensors, systems, and applications to a real-time analytics environment where it can be mined for insights. As we’ll explore in further blog posts, this continues to be a daunting challenge for technical leaders across industries.
In the meantime, the next time you hear the assembly line whirring or see wind turbines spinning, make sure to stop and reflect on the astonishing explosion of machine data – and how it will transform the way we do business in the very near future.
How Equalum can help
Equalum is the first Data Beaming platform, relied upon by enterprises across industries to seamlessly teleport operational data to real-time analytics environments. Built for scalability and ease of use, Equalum’s Data Beaming platform ingests, processes and transforms data in real-time from any number of data sources, before streaming it to any number of target applications or systems. Data Beaming technology harnesses the power of Spark in an end-to-end, enterprise-grade solution – helping organizations rapidly accelerate past traditional ETL or open-source implementations.