Get the Essential Guide to Machine Data
Digital Exhaust. Log Files. Time-Series Data. Big Data.
Whatever you call it, machine data is one of the most underused and undervalued assets of any organization. But some of the most important insights that you can gain—across IT and the business—are hidden in this data: where things went wrong, how to optimize the customer experience, the fingerprints of fraud. All of these insights can be found in the machine data that’s generated by the normal operations of your organization.
Machine data is valuable because it contains a definitive record of all the activity and behavior of your customers, users, transactions, applications, servers, networks and mobile devices. It includes configurations, data from APIs, message queues, change events, the output of diagnostic commands, call detail records and sensor data from industrial systems, and more.
The challenge with leveraging machine data is that it comes in a dizzying array of unpredictable formats, and traditional monitoring and analysis tools weren’t designed for the variety, velocity, volume or variability of this data. This is where Splunk comes in.
Machine Data Analytics
The Splunk platform uses machine data—the digital exhaust created by the systems, technologies and infrastructure powering modern businesses—to address big data, IT operations, security and analytics use cases. The insights gained from machine data can support any number of use cases across an organization and can also be enriched with data from other sources. The enterprise machine data fabric shares and provides access to machine data across the organization to facilitate these insights. It’s what we call Operational Intelligence.