During its daily operation, the Service Desk generates a large amount of data. Every incident or request contains information about the service, category, creation and resolution times, SLA, and other attributes. Individual records can therefore serve not only to resolve a specific request, but also as a source of information about the long-term performance of IT services.
To work with this data outside the Service Desk itself, it needs to be made available in a suitable way. This is where OData comes in. This interface makes it possible to access data from SMAX in external tools and process it further. One such tool is Power BI, which can be used to create custom analytical views based on this data.
Data from SMAX can be loaded into Power BI via OData, where it can be used to build a data model for further analysis. This allows us to define custom metrics, work with different time periods, filter data by services or categories, and combine different views.
Power BI makes it possible to move from individual records to an aggregated view of the data. At the same time, Service Desk data can be combined with other sources to provide a broader context for IT operations.
This brings us back to the questions we asked at the beginning.
For example, we can identify which services place the greatest workload on the Service Desk. Not only by looking at the total number of incidents, but also at how that number changes over time or how long those incidents take to resolve.
We can also track which types of incidents keep recurring. If a particular category consistently represents a significant share of requests, it may be worth looking into the underlying causes and considering whether there is an opportunity to change a process or introduce automation.
Another perspective comes from resolution times and SLA performance. In Power BI, we can track their development over time, compare individual services or periods, and look for relationships between incident volume, incident structure, and resolution times.
The purpose of connecting SMAX, OData, and Power BI is not simply to create another dashboard. More importantly, it makes it possible to work with operational data in a broader context and track how it evolves over time.
The result can be a clearer view of the workload of individual services, recurring incident types, or changes in SLA performance. Service Desk data can therefore serve a broader purpose – not only supporting day-to-day operations, but also providing a basis for managing and continuously improving IT services.