The rapid pace of digitisation is fundamentally transforming the need for data analytics. As such, businesses need to rely on new data sources, such as machine-generated data vs. traditional structured data.
Insight into such data in real time is what gives companies the competitive edge they need to succeed. Machine-generated data is one of the fastest growing and complex areas of big data, it’s also one of the most valuable, containing a definitive record of all user transactions, customer behaviour, machine behaviour, security threats, fraudulent activity and more. Operational intelligence from machine data gives you a real-time understanding of what’s happening across your IT systems and technology infrastructure so you can make informed decisions.
For example, with operational intelligence developers can rollout new applications and services across mobile and cloud faster, application managers can improve the uptime and performance of online and mobile applications and customer experience teams can look at customer interactions across channels to drive higher conversions and revenues.
Operational intelligence is also the foundation for Big Data security solutions which can adapt to advanced threats and changing business demands. Simple monitoring of traditional security events is no longer enough – in today’s connected world, all data is security relevant. Pre-filtering data or limiting security insights to a pre-defined set of correlations is a recipe for disaster. Security practitioners need broader insights from new data sources generated at massive scale across IT, the business and in the cloud.
Operational intelligence can help stay ahead of external attacks, malicious insiders and costly fraud demands. Through continuous security and compliance monitoring and fast incident response, operational intelligence enables businesses to detect and respond to known, unknown and advanced threats.
The nexus of cheap storage and computing is enabling organisations to harness insights from data that were never possible before. It is also democratising access to data – enabling more users across the organisation to gain valuable insights from it. The question is, how do you unlock operational intelligence?
Traditional approaches and data management are hindering organisations in the quest to unlock insights from their own data. While traditional approaches are great for uncovering what’s known, they fail to discover new insights – the unknown knowns. Another shortcoming is latency as too much time lapses between data and insight. Most of the data today is unstructured machine data, which is generated outside an organisation. This makes it difficult to capture the data and make it available for analysis easily.
A modern approach to analysis enables users to ask any question of the data and analyse outcomes in real time. In some cases, insights delivered an hour late are missed opportunities and so more and more organisations are looking to gain insights from their data in real time to be more agile and responsive.
Machine data is going to grow exponentially, which is a change that IT decision makers should take as a given. The question then is what to do with this data; how to mine it effectively and in a timely manner to deliver new insights for the business that were never possible before. IT leaders should explore methods to combine new sources of data with existing sources to discover new insights that prevent cyber security attacks, reduce fraud or improve customer experience.
Tapan Bhatt is VP of solutions marketing at Splunk
