• Posting in this question here as well, to try to gather a response: HI Folks, We are trying to work on gathering metrics for the Glossary to meet corporate requirements. I spoke with a couple of our Developers on Friday afternoon. Found out our company uses "DataDog" to gather metrics on what I call the "Data Catalog" side of the DataHub tool. We can see via Amazon's "OpenSearch Service", there are "CloudWatch" Logs which are enabled... i.e. Slow Search Logs, Index Slow Logs, Error Logs. What is not enabled are: "Audit logs". Based on John Joyce's suggestion: Use "datahub_usageevent index" to find the information we are looking for..... Our company's Developer has the following questions: 1) Can all of these logs be strung together via "Splunk"? (I am guessing so he can locate this specific index and other useful information in one massive Splunk based log file to exact all of the various metrics we want to gather from one log) 2) Our Development team is more comfortable with DataDog vs OpenSearch.....can they use DataDog vs Kibana/ElasticSearch? ===> Thank you for any ideas or methods anyone has used to gather metrics specifically about the GLOSSARY inside of DataHub. We don't care at this point if the metrics are displayed inside of DataHUb, we just want to gather details like: Number of users • Number of users with > 1 search ◦ > 5 searches ◦ > 20 searches ◦ Re-evaluate with more data the exact numbers • Number of distinct site visits? ◦ TBD - Who is coming back for more searches? • Total searches per week ◦ Per Month ◦ Per Quarter ◦ Per Year ◦ Lifetime • Average searches per user ◦ For users with >0 searches ◦ Can use # of new hires as denominator to see how good the adoption rate is during orientation ▪︎ Can we pull Hire Date and match against email? ▪︎ Parking lot • Number of searches for a particular term ◦ See what’s most popular (misunderstood) • Number of terms • Number of edited terms • Number of edits by term ◦ Has one term been edited or contested multiple times ◦ Rejected Edits will be reportable via Jira • Average number of terms added per month ◦ Per Quarter ◦ Per Year • Number of Glossary Requests (Jira) for new terms (Slack for now) • Number of searches with no results • Glossary downtime

Hi Pam! Chatting with John now - sounds like you two are sorting out details via DM - glad to hear it!