Machine data is any and all digital information created by computers, mobile phones, embedded systems and other networked devices. Machine data comes in an overwhelming array of unpredictable formats. The variety, velocity, volume or variability of this data have over the years made it very difficult for businesses to harness and convert it to valuable insights using traditional monitoring and analysis tools.
However, since the advent of big data management technologies such as Hadoop and Splunk, it is now much easier to read and digest machine data than ever before.
Some examples of machine data include application, server and business process logs, call detail records as well as sensory data. Internet clickstream data and website activity logs can also be considered a part of machine data.
When machine data is combined with other enterprise data technologies for analysis, it can then be used to provide the business with views and insights on improving business activities and operations.
Large industrial manufacturers use machine data to analyse the performance of field equipment in near-real-time, which they then combine with historical performance data. This helps them to better understand service problems as well as predicting equipment failure and equipment maintenance issues before machines break down.
Machine data is also used to assist with the setting up and monitoring of oil and gas pipelines, or with natural disaster warning systems based on feeds from marine sensors. They can be used in weather forecasting systems that take data from satellites and weather stations for isolated regions. They are also used to assist with building energy management systems and elevator data to improve efficiency.
We can expect to see more use cases as applications for machine learning begin to take a foothold in society.
