The Wedia Analytics module is based on the Elastic engine and allows analyses of real-time data.
Prerequisites and installation
The storage and request of the events of the application is ensured by an Elastic server .
It will therefore be necessary to have a Elastic server in order to be able to store and view these statistics.
In addition to storage in Elastic all events are logged in a log file located in the administrative directories of Wedia and allow you to replay events if necessary.
Elastic Server Installation
The basic installation consists of downloading the latest version of Elastic 5.x or 6.x since and start it on a server.
The ElasticSearch instance can be deployed locally on the Wedia server or on any other server accessible by the latter. It is also possible and advised in production to deploy an entire ElasticSearch cluster.
You will find more information on installation, parameterization and configuration tuning Elastic on the site of link: official documentation for your version.
Caution | Only versions 5.x and 6.x of Elastic are fully supported by Wedia at this day. Please do not use 1.x versions anymore. |
Once the Elastic server is started, just go to the system settings of WXM /admin/ebnAdministration.ebn and to enter the following information the URL of one of the Elastic servers and the prefix to be used for storage statistical events.
Analysis configurations
A configuration can be defined as an entry point in the analytic system for storing events.
A configuration is always constituted of :
a configuration name,
series of events.
Events are made up of:
a timestamp
a set of parameters defined by the system known as
contextual parametersand are common to all events.a set of event-specific parameters
Dashboards
Analysis results are displayed in dashboards that can be used to can be viewed via the analytics action of the back-office V3 at the URL /wcm.jspz?form_action=analytics.
These dashboards make it possible to view the results of analyses for different evaluation configurations that exist in the system.
The buttons for accessing the dashboards allow you to navigate between the different statistical dashboards.
Clicking on the date allows you to access the calendars that allow you to set the date of the statistical period.
Statistics are always displayed over a period of time. The default time period is 30 days.
Note | Regardless of which graphic components are used on the different paintings they are always attached to a period of time. If the time period is changed by the user then all the graphical components will be updated with the period data. |
Data vizualisation
Statistics data can be viewed in several ways according to requirements via graphic components:
in the form of histograms allowing to visualize the events of events over a given period at fixed time intervals. For example, see the number of daily connections for the current month.
in the form of allocations allowing to visualize groupings of events over the period according to a given criterion. For example, view the different languages of the users' logon over the period. These distributions can be represented as pie charts, graphs in columns or tables.
in the form of counters allowing to visualize a number relative to the events over the period. For example, the number of different users over the period.
in the form of tables allowing to visualize events such as that they were recorded in the system.
Histograms
These graphs can be used to represent the events as they have occurred over a given period of time at regular intervals.
This histogram shows the DAM activity on the month of january 2019.
The time interval here is one day. Each column represents all the events that happened every single day.
Interactions with the graphical component
Clicking on a column will adjust the viewing period from the dashboard to the period represented by the column.
It is also possible to select a time range directly on the graph by clicking on the graph and moving the mouse. The highlighted area will represent the new time period.
Whichever method is used, the new time period will then be updated and the dashboard will be redesigned by taking into account only the events that occurred during this period.
Data distributions
These graphs are used to represent distributions of data in events recorded in system configurations.
For example, if you want to visualize the distribution of connections by role to the system it will be possible to choose the representation by this type of graph by displaying the result as a pie chart.
The distribution graphs can be presented in different forms.
Pies
Columns
Tables
If it is present, the user will be able to change the representation mode (pie|column|table) by choosing the display mode that corresponds to him most in the dropdown list.
Interactions with graphical components
The components are interactive and it is possible to click on the results to add filters to all dashboard graphics components. As previously seen on the histogram graph where clicking on a column allows you to refine the results period, here clicking on an element allows you to add an event filter.
By clicking on the Download of the action pie for example (or column Download on the graph in columns or line Download of the table), the dashboard will be automatically updated by displaying only events related to the Download action.
Clicking on the label in the legend will exclude results events.
It is possible to combine filters by clicking on the results of a graphical element then by clicking on the results of another graphical component. Filters will be combined to each other.
Active filters are displayed at the top-left side of the screen.
Tip | Green filters indicates that only results having the given criteria are displayed in the current dashboard. Red filters indicates that results having the given criteria are excluded from the current dashboard |
Simple values
This component displays a simple event counter. It is possible to count either the total number of events according to a criteria over a given period of time or the number of separate events on the same criteria.
For example, the first can be used to count the total number of connections on the system, the second can count the number of different users who have logged on the application.
