Monitoring and usage analysis in SAP Analytics Cloud
For every reporting and analytics system whether we are running it on the cloud or on premise the requirement to analyse and monitor the user activity ,understand the user behaviour and get the overall analysis of which reports ,KPIs and fields are in use is a crucial part of realizing how well is our system is working.
Analysing the usage is one of the useful administration activities as it provides us a clear view about:
- User acceptance of the system
- Grow over time
- inactive users
- optimised license management
- optimise fun functional roles assignment
- Most /least useful reports
- User activity
In this blog I will cover the system monitoring and user analysis capabilities and additional resources that can provide you all the information you require.
System Monitoring is an integral part of SAP Analytics Cloud and can be accessed through the System –> monitor menu
The monitor is structured from four different tabs and provides useful information about license management and storage which can be useful as per your plan you first of all paying for licenses and unused licenses means you can free them to other users and 2d of all – you can reduce your expenses.
Licensing can be tricky as you know so for further details suggest to start here :
In the monitoring there are four main views :Overview ,system usage by storage ,system usage by user and trace
I will focus in the two first tabs as I find them the mist useful ones
This tab is a dashboard which shows four main ares :
In this bullet chart you can see the current license status per planning ,Business Intelligence and Analytics hub (which will change it’s name to content catalog) – there is no actionable options in case you are getting to your threshold limits but the color will change accordingly
And in case you have a critical threshold met the bullet chart will use the color red correspondingly
There are two more useful time series line charts that reflects the activity over time
Number of Active users
This chart provides the standard time filtering that comes with time series and shows active users over time which aligns with the licensees bullet chart
So if you compare the active users to the bullet chart corresponding you will get the same number
Number of Logins
Number of logins will show you the login trend overtime which is another standard view which in person I don’t find as that interesting unless you can view unusual picks ,compare it to normal behavior or get alerts when there an impact to the system performance
System usage by storage
This tab can basically help you to analyze and find out which models and users are using large/above normal amount of storage .Like the other views there is no threshold or a line reference that can focus the data displayed in the charts but it’s a good start to find out about the models and users ,once we sort the two charts it will be easier to view the data
So it can be a good practice to focus in models which are more than 20MB and find out regardless to the small amount – is that a model that wasn’t build in the right way or not suited for the usual aggregative display and may require more manipulation in the data preparation level
the next view is the storage per user which can be useful if we focus in users with un usual storage activity that might imply on duplication of versions or missing steps in the data preparation and might help us improve the user experience and improve his data model, in person I would add correlation between the user to the data model storage or at least drill into the model level so I can identify more easily the main objects behind the overall number, search to insight would work well here
The monitoring provides two more tabs which are the system usage by user which shows in a table view the number of transactions per user and the trace tab that can provide log level details for errors.
For advanced tracing options I recommend reading note 2630653
The trace level can be configured from the system administration and it’s basically defined by the level of severity :
Usually the log level Error is used for the tracing but can be changed accordingly
other then that it’s recommended to delete the log files after a period of time using the delete option which offers several intervals doe log deletion ,currently this task can’t be scheduled but still easy to maintain it:
The log file is limited to a maximum of 350,000 rows of data. The oldest log entries will be deleted to maintain this limit.
Content and usage analysis
SAP Analytics Cloud also provided lately a content package that can be imported and the data model and stories packaged inside of it can be used for further in detailed analysis of the users ,models and stories.
This package is available through the content network :
Once you access that menu entry you can further access the samples tile and open it
here you can find a package name :SAP Analytics Cloud Usage Tracking Content
Once you click on that package a window will popup and provide you information about both the package content and the import options .
In the overview tab there is also a description of the models included
In the Import options you can choose the import option and view the content included in this package, use overwrite objects and data if you require overwriting the existing content
While importing the package you can see both it’s progress through the notification center :
And once the import have been completed you can verify it’s content :
So now we can access the SAC content usage dashboards which will now display your system data in three different tabs :
Story Information :a variety of different charts types are available here and provide different views of the story per views ,number of stories per user/folder, top viewers and oldest accessed stories :
Model Information :this tab displays another set of dashboards displaying different views about the model usage :top models ,models per user ,least used models and overall list of models created
User Information : this tab is the richest in terms of different views and detailed level :you can find activity per user and most active users per logins :
You can also find a similar chart to the one that displayed in the monitoring and analyzing user logins over time only without the license type dimension :
Adding new insights
So the overall usage is quite comprehensive as well as it’s standard ,how can we add more useful insights to the existing usage analysis ?
So first we need to understand the model views and how they connect and or can connect to each other.
Through any usage tab you can check the model components and how they are connected :through the designer panel link dimension you can see the joins between the model views :
There are four main models :
- Users usage
- Usage activities (e.g:create ,delete ,execute, login)
- Usage of other objects
- Usage files – additional information about files (mainly used in the story information tab)
This link dimension window can show us what exactly do we need connect if we want to add a linked model to an existing story and it’s charts
One thing I haven’t found in the those three tabs is which models have the biggest audience :how many users are using each model ?
In order to answer that question I will add under to the SAP_SAC_USAGE_USERS data model the SAP_SAC_USAGE_FILES model which contains the information about models
I will link the dimensions according to the suggested linking which matches the model linking structure ,now I will be able to use dimensions and measures from the different models :
In the chart properties I will add as a measure count of users ,the description field as the model name and filter the File type on Model
The result will be a bar chart that displays the users per model :
Search to Insight can be used as well in order to get quick answers and insight across the different models
It would definitely be more sufficient if search to insight would work here on the entire linked set of models to enable cross model questions ,still it’s one of the most intuitive quick ways how to gain insights with minimum effort
The monitoring and the usage analysis provides good overall outlook on what’s the current and historical activity across the systems and provides the administrators the right and up to date insights.
Comparing to other solutions such as the auditor universe & reports for SAP BI and the CMC cockpit this solution and model and more flexible.
It’s important as well as it’s basic to know the different data models, their main key dimensions and how to connect them ,you can definitely build and create your own views that will provide an added value when you perform cross model analysis
For additional reading I recommend to go through the following links :
Hope you find this article helpful and as always I encourage you to leave comments ,ask questions and continue the discussion