
TRAINING
Engineering Software Administration
and Optimization (ESAO)
- Registration Deadline: September 1, 2026
| DURATION | TRAINING TYPE | TIME | LANGUAGE | PRICE |
| 4 days | Virtual/Online | 3:00-5:30 PM CET | 8:00-10:30 AM CST | English | $990 |
Start your Open iT Training journey with this course on Engineering Software Administration and Optimization, in which our team of experts will equip you with the best practices and processes to get the most out of your software investments.
Master the ins and outs of managing the Open iT Core Reporter and/or Analysis Server. Explore various topics around License Administration. Get expert guidance on licensing infrastructure best practices and efficient license management to optimize applications usage. Acquire hands-on experience on the best practices in license management and usage optimization, with a practical output that you can take back to your company.

Most organizations do not overspend on software because of poor budgeting. They overspend because they lack visibility into software usage, license usage, and actual usage data. In our previous articles, we explained how concurrent licensing works and what usage data reveals about real demand. Now, the focus shifts to action through concurrent license optimization. This is where software license usage reporting tools

Fragmented software licensing continues to undermine federal software asset management (SAM) across U.S. agencies, limiting visibility, increasing compliance risk, and generating avoidable spending. Despite policy frameworks and ongoing efforts in federal IT management, many organizations still lack the data needed to support effective software license optimization in federal environments. Strengthening federal IT procurement strategy and leveraging GSA software

Software asset management (SAM) has traditionally spanned multiple governance disciplines — software inventory, entitlement management, compliance oversight, and license usage monitoring. In engineering environments, organizations have long relied on license activity metrics — feature checkouts, runtime sessions, or peak use — to understand how high-value technical software is being used. While these metrics offer operational visibility, they
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