OpenLM Reporting Hub vs Embedded Reports Comparison

Can the Reporting Hub produce the same reports as the OpenLM User Interface? #

Indeed, the OpenLM Reporting Hub has been structured with the measures-dimensions structure in mind, which is currently the industry standard for BI-friendly databases.

This structure allows for building the same reports as in the OpenLM User Interface.

But, the OpenLM Reporting Hub uses Power BI, which allows for endless customization of your created reports.

So you could effectively create an infinite amount of reports and dashboards, in order to exactly match your reporting needs.

Please see the list of reports:

Report

OpenLM User Interface  OpenLM Reporting Hub
License Usage Link Link
License Activity Link Link
Denials Link Link
Project Usage Report Link Link
Group Usage Report Link Link
Feature Usage By Group Link Link
Feature Usage By User Link Link
Licenses Link Link
Licenses Not In Use Link Link
License Utilization Link Link
License Procurement Link Link
Currently Consumed Licenses Link Link
Active Users Link Link
Dashboard Link Link

 

So what else can the Reporting Hub achieve? #

  • Data aggregation by country.
  • Hierarchical groups reporting.
  • Transaction report (denials + sessions).
  • Denial percentage report (denials/transactions).
  • Usage report combined with denials.
  • License utilization by time.
  • Daily token usage.
  • Drill down to all dimensions.
  • Idle sessions reports.
  • Actual usage (Sessions duration – Idle time).
  • Global vs local license analysis.
  • Management dashboards (Simple overall status report).
  • Working hours data aggregation.
  • Custom-made KPIs.
  • Follow the sun – utilization per time zone.
  • Drilled denials report.
  • Many more reports, as the Reporting Hub is fully customizable.

 

See general documentation on the OpenLM Reporting Hub (see video at the bottom): #

https://www.openlm.com/knowledge-base/openlm-usage-analytics-and-customized-license-reporting-kb4060/

 

See the data structure of the OpenLM Reporting Hub (see video at the bottom): #

https://www.openlm.com/knowledge-base/12016/

 

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