User Activity as a Thorough Audit Trail

Traditionally, exploring recorded database user activity data requires a "one-at-a-time" approach. This can bring some clarity when it comes to individual databases, but overall trends remain in the dark due to the time factor and the lack of practical reporting capabilities.

databaseEZ includes a special built-in tool—the User Activity Analyzer—that lets you parse and display detailed recorded user activity information for multiple databases on a server all in one central interface.

Put recorded database user activity data to use in a scope that is unthinkable in any native solution:

• Identify users who have accessed given databases during a specific time frame, and see what types of actions they took.
• Easily create detailed usage activity reports based on a summary or average of read, write, update or delete actions per database or user.
• Find the most and least frequently used databases on a server using a special usage grading system.
• Track the usage of the users that matter: easily weed out server, agent signer, or administrator usage to focus on what’s important.
• Enable/disable user activity, or mark it as confidential across multiple—even all—databases on a server.

* Please note that databaseEZ relies solely on the Notes C API to gather these properties and does not circumvent IBM Notes and Domino security.

databaseEZ lets you access and analyze recorded database usage activity across multiple databases on a server. But how do you translate this data into application usage frequency? Because recorded usage activity is strictly limited to 1400 entries, there 3 hours for some heavily used apps, while it might even be years for others. And thanks to versatile analysis capabilities, it's easy to get a handle on usage frequency patterns for all of your databases.

Recorded database usage activity is a very rich source of data—if you can get to it. databaseEZ's User Activity Analyzer gives you access to more than what you see in your native clients, allowing you to get specific counts for reads, writes, updates, and deletes. What's more, your results are further separated into Data (documents) and Non-Data (designs, ACLs, etc.) counts so you can easily create a variety of usage reports, such as average reads per application or user, to better understand your global usage patterns.