All your IT applications, systems and technology infrastructure generate data every millisecond of every day. This machine data is one of the fastest growing and most complex areas of big data. It’s also one of the most valuable, containing a definitive record of all user transactions, customer behavior, sensor activity, machine behavior, security threats, fraudulent activity and more. Making use of this data, however, presents real challenges. Traditional data analysis, management and monitoring solutions are simply not engineered for this high volume, high velocity and highly diverse data.
Making use of this data, however, presents real challenges. Traditional data analysis, management and monitoring solutions are simply not engineered for this high volume, high velocity and highly diverse data. Consider traditional information management systems, such as business intelligence and data warehouse tools. These systems are batch-oriented and designed for structured data with rigid schemas. IT management and security information and event management (SIEM) tools, on the other hand, provide a very narrow view of the underlying data and are hard-wired for specific data types and sources. They also don’t provide historical context.
Finding a better way to sift, distill and understand the vast amounts of machine data can transform how IT organizations manage, secure and audit IT. It can also provide valuable insights for the business on how to innovate and offer new services, as well as trends and customer behaviors.
Splunk Enterprise is different from previous approaches to managing, auditing, securing and gathering intelligence from IT systems and technology infrastructure. Here’s how: