18 Jul

A.A.A.R. v4.4 with a new Data Quality dashboard

During the support activities on the A.A.A.R. solution, one of the most common request is about the success (or failure) of the extraction task from Alfresco. As a standard Business Intelligence solution, the extraction task is developed as a batch (called ETL process), in average executed during the night time.

How can you be sure that the extraction from Alfresco succeed or failed?

And how can you be sure that all the audit trail, the documents, the folders and workflow instances are correctly available into the analytic environment?

For those purpose, the brand new A.A.A.R. v4.4 release has been developed, together with some minor improvements you can fin detailed here in the change log.

Two in one

In this v4.4 release the relevant features are mainly two:

  1. The Extractions log.
  2. The Data Quality panel.

Both the features are a helpful support to the Administrator, to control IF the scheduled extractions succeed and IF all the Alfresco’s data are correctly available into the A.A.A.R. Data Mart. All of this, without technical tasks, in a easy and automatic dashboard.

The Extractions log

The Extractions log is developed as a dashboard, available directly in the A.A.A.R. Wizard. In the dashboard you can filter: the Alfresco instance, the period of the extractions and, as the last selection, a single extraction. Once the extraction is selected, you can view two different panels: the first describing the logs of the various tasks composing the data extraction and the second describing a Data Quality evaluation. In the extraction log panel, is presented:

  • The name of the task (referring to audit trail, documents, folders, workflows).
  • The duration of the task (starting date/time and ending date/time).
  • The result (succeed in green or failure in red).

Below a video describing how to use the dashboard.

The Data Quality panel

As you can see from the video, below the extraction log panel another panel describes the details of the entities extracted and available into the A.A.A.R. Data Marts. For each entity, it’s presented a number representing:

  • The total number of entities counted into Alfresco.
  • The total number of entities counted into the Staging Area (repository used by A.A.A.R. to extract the incremental data from Alfresco).
  • The total number of entities counted into the Operational Area (repository used by AAAR to transform the incremental data from the Alfresco format into the Analytic format).
  • The total number of entities counted into the A.A.A.R. DataMart (final repository of the available data to analytics).

If the total number of entities counted into Alfresco are equal to the total number of entities counted into the A.A.A.R. DataMart, we can be reasonably sure that all the data are migrated and available in the target repository (A.A.A.R.). To make easier this check, a green OK tag describes the success of the check and a red KO tag describes that something should be checked.

Below a simple example describing how the panel is showed in case of failure of Data Quality checks.

data quality check with errors

Last but not least, which are the available entities included into the Data Quality panel? Below a complete list for a better understanding.

  • Actions in the audit trail (if activated into Alfresco).
  • Alfresco nodes of the cm:content type (and all the defined subtypes).
  • Alfresco nodes of the cm:content subtypes, requested to be extracted as custom types (you can read here for further details) .
  • Alfresco nodes of the cm:folder type (and all the defined subtypes).
  • Alfresco nodes of the cm:folder subtypes, requested to be extracted as custom types (you can read here for further details) .
  • Alfresco nodes of the aspects requested to be extracted (you can read here for further details) .
  • Activiti workflow instances.
  • Activiti workflow tasks.

Trust only in your eyes

Concluding, the new A.A.A.R. v4.4 release is more stable than ever. Not only because is used to analyze big Alfresco repositories but also because helps the Administrator to have a trusted analytic repository for the Knowledge Workers (the final users). Enjoy and give me feedback… please. 🙂

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