A Splunk query is used to run a specific operation within the Splunk software. A Splunk query uses the software's Search Processing Language to communicate with a database or source of data. This allows data users to perform analysis of their data by querying it. It can be compared to SQL in that it is used for updating, querying, and transforming the data in databases.
Splunk's query language is mainly used for parsing log files and extracting reference information from machine-produced data. It is especially useful for companies who have a number of sources of data which need processing and analyzing simultaneously, to produce results in real-time. Splunk is specifically created for dealing with the kind of log files that machines create and making them human readable.
Splunk's mission statement is "to make machine data accessible, usable and valuable to everyone". With the huge increases in machine data being produced by the IoT (Internet of Things) and IT infrastructure, this makes it an important contributor to the field. The Splunk API, which has a web-style interface to input a Splunk query, allows data users to search, monitor, and analyze machine-produced big data.
There are a few reasons why machine data makes processing and analysis difficult:
No predefined schema.
Large amounts of unstructured data.
Wide divergence in the technology systems generating it, which can include networks, sensors, applications, devices, and servers.
Produced data and possible formats are extremely unpredictable.
Splunk makes considerable use of AI and machine learning to deliver more intelligent results to a Splunk query. This gives users the opportunity to better visualize the data that they are creating and what it means for their business. It also allows companies to scale up their data analysis operations as their needs get larger.