improved documentation

README.md

 # Data Analytics
 
-| qa | master |
+| [qa-v0.4](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/qa-v0.4) | [v0.3](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/v0.3) |
 | :-: | :-: |
-|[![pipeline status qa](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/qa/pipeline.svg)](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/qa) |[![pipeline status master](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/master/pipeline.svg)](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/master)|
-|[![coverage report qa](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/qa/coverage.svg)](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/qa)|[![coverage report master](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/master/coverage.svg)](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/-/commits/master)|
+|![](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/qa-v0.4/pipeline.svg) |![](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/v0.3/pipeline.svg)|
+|![](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/qa-v0.4/coverage.svg) |![](https://gitlab.cern.ch/cloud-infrastructure/data-analytics/badges/v0.3/coverage.svg)|
 
 The project contains a suite of tools to run data analytics pipelines on the monitoring data of the CERN Cloud Infrastructure.
 
@@ -26,25 +26,27 @@ The CI/CD of this project is used to:
 1. Build Docker images with pre-installed libraries needed for the project's scope
 1. Run functional tests of the Data Analytics' pipeline, and its components
 
-The repository contains extensive documentation of each subfolder in the README file included in the specific subfolder.<br>
+The repository contains extensive documentation of each subfolder in the README file included in each subfolder.<br>
 This is a guide map of the repository:
 
 1. ETL libraries ([etl](etl))<br>
    Implement the extraction of data from the different monitoring databases: InfluxDB, ElasticSearch, HDFS
-1. Tests suite ([tests](tests))<br>
-   Unit tests of the ETL libraries, test pipelines' components
-1. Javascript Grafana extension ([grafana_extension](grafana_extension))<br>
-   Implement an extension of the Grafana Annotation panel, modifying the Grafana JS code
 1. Anomaly detection libraries ([adcern](adcern))<br>
    Implement anomaly detection Models, based on pyOD, traditional ML and DL methods
+1. Tests suite ([tests](tests))<br>
+   Unit tests of the ETL libraries, test pipelines' components
 1. Docker image definition ([docker-images](docker-images))<br>
    Dockerfiles for images used in this project
 1. Airflow-based Anomaly Detection System ([control_room](control_room))<br>
    Setup and run the Anomaly Detection System
+1. Javascript Grafana extension ([grafana_extension](grafana_extension))<br>
+   Implement an extension of the Grafana Annotation panel, modifying the Grafana JS code
+
+All these components are needed to deploy the Anomaly Detection System described in the figure
+<br><img src="documentation/images/AD_system_technologies.png" width="70%"><br>
 
 ## From where to start
 
 1. For a general introduction on this activity see the [ITTF seminar](https://indico.cern.ch/event/1012703/)
 1. For interactive examples see [examples](examples)
-1. For Airflow deployment see [control_room](control_room))
-
+1. For Airflow deployment see [control_room](control_room)