One of the biggest challenges that we see organizations facing when it comes to trying to get their collective heads around software asset management is the age old issue of “garbage in, garbage out”. Data collected from many different sources simply does not go far enough in terms of analyzing and classifying each piece of software.
Most IT Asset Management tools use a global dictionary of software items to classify detected software. Vendors spend significant resources on maintaining and keeping their software dictionary up to date and sending customers updates to the dictionary (think – Antivirus). As SAManage is a SaaS based service, we have taken a different approach to building and maintaining our dictionary – an approach that delivers significant benefits to our customers.
With SAManage, the dictionary is self-populated. Any time a new piece of software is detected at any of the customers utilizing our platform, it is analyzed and added to the dictionary, making sure that it is always up-to-date. When new software is detected, it is classified and categorized so that the next time it is detected at any other customer site, the properties automatically get pulled directly from our dictionary.
We have also developed our own proprietary algorithms that classify new software and maintain the accuracy of the software dictionary based on certain properties in the software title and manufacturer fields. The data classification process is responsible for grouping stand-alone applications (“Microsoft Word”) into suites (“Microsoft Office”), assigning the correct category, tagging software and correcting manufacturer names (a common issue with software inventory management). The classification engine is also responsible for marking system software such as drivers, patches and fixes as such and eliminating them from the software inventory, making it easier to view software inventory that is not cluttered with system software. This is a major pain point with many software inventory tools that simply report all-installed-software.
Our internal studies shows that about 70% of the software installed on a typical Windows machine has to do with “system software.” Automatically excluding all system software is an extremely important step in making sure that the software inventory database is an actionable repository of trusted information.
At SAManage we also use the software dictionary for the purpose of detecting risks and greynet titles that do not belong in an enterprise environment, such as games, P2P file sharing tools, crackers, etc. We have processes that scan the software dictionary and determine if software is a risk/greynet and mark it as such. When that software is then detected within any of our customer’s software inventory, a new risk is created for the administrator to take action and remove that software from the affected computer. The same approach is used to make sure all computers are running up-to-data antivirus protections as well as detecting additional risks.
The overall approach of using a centralized data repository consisting off an aggregated view of all the software installed and used by our customers (essentially “crowd wisdom”) ensures that our global software dictionary is always up-to-date and constantly improves the data quality for all of our customers. This provides a significant benefit over tools like SCCM/SMS and others who only collect the inventory and do not have the ability to normalize and classify it into actionable data.Software Asset Management – The Importance of Data Normalization Click To Tweet