The three phases of data analysis are input, insight, and impact. These are explained below.

1. Input: Inputs are nothing but different sources of data. These include various location data, transactional databases, social media data, mobile application data, data obtained from various databases, IoT sensor data, and so on.
   rubiflow and rubithings are used to connect the data with the application (Refer to rubiflow or rubithings).
   
2. Insight: Insight is that part of the rubiscape platform where the data is stored, cleaned, aggregated, and analyzed to produce graphical output. The three main processes that take place in Insight are  - Data Integration, Data Science, and Data Visualization. These three processes are described below.
   1. Data Integration - Data integration emerges from complex data center environments where multiple systems are creating large volumes of data. This data must be understood in an aggregate form, rather than in isolation. The aggregated data can then be used for predetermined analytical operations. On the rubiscape platform, once the data is connected to the application, it is essential to store the data. Depending upon the type of data, the data is stored in data repositories like Social Media, Email, Web Pages, IoT Edge, Data Lake, NoSQL, and Events.
   2. Data Science (Processing) - Data processing is the extraction of actionable insights from input data using a variety of techniques. In rubiscape platform, there are three modules for data processing, namely, rubiML, rubitext, and rubicast.
   3. Data Visualization - Data Visualization is the representation of data in graphical form. On the rubiscape platform, rubisight is a dashboard to see models and other results using a simple drag-and-drop functionality.
      
      
3. Impact: Impact is the last phase where the processed data is accessed and seen on different applications (including mobile applications), dashboards, chat bots, and so on.