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The Data Studies allows you to configure quite sophisticated queries on top of your recorded session data in order to answer deep-dive questions on correlations in your data to gain deeper insights.


By default the Analytics client presents aggregated data to the end user. While this meets many of the analytical needs of the user it is sometimes beneficial to view the raw data that has been transmitted by the application. The Analytics client allows for the type of acces through the Data Studies. Specifically, using the Data Studies allows the user to perform filtering actions on raw (vs. aggregated) data. Because queries that are run against raw data may be slower (based on number of filters applied etc.) the Data Studies allows the user to create jobs and let them finish asynchronously.

The major benefits of the Data Studies are as follows:

  • Simplified advanced query builder dialog
  • Query icon visible in the widget to improve discoverability
  • Queries are saved
  • Saved queries can be rerun
  • Saved queries can be modified
  • Queries has its own section in the side nav to improve discoverability
  • Query results can be easily modified and rerun

The Data Studies is available on a number of data views and can be found in the Menu link to the far right.


Accessing the Data Study dialog will allow you to retrieve data for the given data view using a much more complex filter setup. The Data Study dialog will allow you to include the following new filters when requesting data:

  • Feature Use filter. Just as you can filter on data collected such as versions and country, you can now filter on the data you have collected your self. You can specify that you only want data from sessions that have used a particular feature by making use of the data you are already tracking. Use this filter to discover changing behavior or correlations between certain feature patterns.
  • Feature Timing filter. You can also use your tracked timing to segment your data. Want to look at the data from users with a slow startup time? With the feature timing filter you can filter on any timing you have integrated into your application tracking. Dive into the correlations between slow startup times and the memory installed or find out if quick report processing also means more reports being generated.
  • Feature Value filter. Similar to filtering on timing aspects you can also filter on the discrete values you have tracked. Using this filter you are able to use your own values as filtering parameters to find out correlations between these values and the data collected.
  • Installation ID filter. Lets you filter for on a specific installation if you have implemented an installation ID when integrating the monitor.
  • Cookie ID filter. Similar to Installation ID but this is an anonymous identifier.
  • IP Address filter. Allows you to filter on sessions coming from a specific IP address.
  • Origin filter. Allows you to filter on public or internal data.
  • Summation filter. Allows you to view the data by daily sessions or daily users
  • Loyalty filter. Allows you to filter on how many times the user has used the application
  • Environment filter. Allows you to filter on environment parameters such as operating system, memory size etc.

These new filters, along with the existing filters, are presented in a new Data Study dialog:


You can add additional filters to your Data Study selecting them in the dropdown. When a filter has been selected it will expand and you can configure the filter to your needs.

Once you have specified the specific filter you want, you can click Run and a report will be generated in the Results view. If you want to reuse your report on other charts you can give it a name in the Save as field in the bottom right corner. When a name has been added your report will be saved and can be easily rerun from any chart. When a report is saved it will also appear the Reports view where you can edit delete and clone to suit you reporting needs.

Creating a Data Study

As you are viewing your data in the client, you can create a specific Data Study by clicking the New study menu item, as seen in the example screenshot below:


Managing Data Studies

Once a Data Study is created it may be managed (edited, deleted) by either selecting the report from the list presented by clicking on the "Data Explorer: Data Studies" side menu bar, or by using the same data view menu that was used to create the study:



Viewing the results of Data Studies

Once a Data Study has been created it is available via the Resuts menu on the side menu bar.


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