SAP Analytics Cloud (SAC): Analyzing Usage / Collecting Statistics
You have setup your connection to BW and organized your content in SAC? Released access for your end users? Time to relax and enjoy your nice self-service data discovery solution? But wait! You might be very interested in the usage and adoption rate of SAC in your company! And this is exactly what we will be talking about in this post:
- What statistics are available in SAC by default
- Download of a ready to use dashboard for SAC
- How you can create a more in-depth analysis of SAC usage
What statistics are available in SAC?
SAC ships with some metrics which can be accessed at System / Monitor. There you can analyze the number of users, logins, consumed storage by model and how many transactions (any activity) a user performed. While this is a good starting point to get a high level overview of your cloud solution you might be interested in a more in-depth analysis.
Gladly SAC has you covered! If you head to Security / Activities you will be presented with a large table of user activities. Nearly any action a users performs is collected and visible in this list. For example which object type (story, model, connection, dimension, user, etc.) has been accessed in which way (read, write, update, delete, etc.) at what time.
For our scenario we are interested in the object types model, story and user with the activities read and login. In the next chapter we will look at how to utilize that data set to create insights.
Download SAC dashboard and model
Please download the provided story and model: Download SAC Usage Analytics Story. Note that this is no official SAP content and comes without any support. The story allows you to analyze how many users you have, how often they log in, what stories are accessed and which models are popular. It allows you exclude certain users (e.g. yourself, admins, etc.) and specify the analyzed time range via story filters.
The content is currently compatible with Wave 16 and 17. If you have trouble importing the
content package drop a comment.
How to create an in-depth analysis
The data is available in SAC, so let’s create something meaningful with it! The following steps must be performed:
1. Export Security / Activities data
2. Prepare the data
3. Create a model
4. Upload the data into the model
5. Create a story to visualize the data
Steps three and five will be skipped here as you can download a ready to use model and story from this post.
1. Export Security /Activities data
Head to Security / Activities. In the upper right corner is a down-facing arrow. Click it to open a download dialog. You can now choose the time range you want to export. I would suggest the last three months but feel free to adjust this to your needs. Please allow a few seconds for generating a CSV export file after clicking download. In the meantime just keep the window open and wait until the download starts.
2. Prepare the data
Open the CSV file with Microsoft Excel. There are three rows which we don’t want: The frist row with some title, the second empty row and the fourth empty row. Delete these rows:
If it did not convert the file to columns you must perform these steps manually. Use the text to column feature of Excel:
The file looks now much cleaner. Just one more step before we can import the data. SAC requires at least one measure. We will call it “Count” and add it as the last column. Fill each cell in this column with a 1 and save the file.
3. Upload the data into the model
Last but not least we must import the data to SAC. If you have downloaded the SAC content package from this post you should have a model called SACStats. Open the model and go to Datasources and upload the prepared CSV file. This will take a few seconds:
After successful import click on the imported draft source in the active panel. This will open the modeler:
Here you can map the content of the CSV file to the SAC model. By double clicking on a card it will expand and show all properties (ID, Description, additional attributes). Please make sure that you always map the CSV fields to the ID field in SAC. If you are finished press Finish Mapping.
Finally you can improve the master data quality for the User dimension. The ID field should be now populated with each user name for which SAC has recorded any activity. The description column gives you the option to enter a more descriptive name (e.g. full name) of the user while the group column allows you to enter user group information (e.g. IT, Sales, Marketing, etc.) for each user. This information is also used in the provided stories. Click save and you are done.
Head over to the imported story SAC Usage Analytics and analyze the imported data.
I hope you enjoyed this post!