Drive effective Splunk enablement and adoption & build user cohorts using internal logs and machine learning [Splunk Enterprise, Splunk Cloud, Splunk Machine Learning Toolkit, AI/ML]

Wouldn’t it be a great if we had Splunk’s version of Moneyball; an application where everyone comes out ahead by leveraging data to drive effective Splunk enablement and adoption? Splunk’s internal logs have a wealth of information about how Splunk is being used within your organization. Let’s take drinking the “Splunk Champagne” to the next level by applying statistics and machine learning to Splunk’s internal logs! This session will cover segmenting users based on their search profiles - number of searches run, average response times, and recency of searches executed, among other criteria. We’ll use techniques such as clustering to classify users from novice to experts, and use TF-IDF and text analytics techniques to understand commands used in search strings. Enriching this data with completed and planned Splunk Education courses, lunch & learn sessions, and other training activities will enable your users to achieve the Splunk Ninja status they’re looking for!

Speaker(s)

Anand Ladda, Staff Solutions Engineer, Splunk

Slides PDF link - https://conf.splunk.com/files/2019/slides/FN1373.pdf?podcast=1577146257