Architecture

Data analytics refer to aggregating, analyzing and presenting information about business activities. This definition is paramount, when designing a solution to address a data analysis use case. Aggregation refers to the collection of data, analysis refers to the manipulation of data to extract information, and presentation refers to representing this data visually or in other ways such as alerts. The WSO2 DAS architecture reflects this natural flow in its very design as illustrated below.

The WSO2 DAS architecture can be broken down into four main modules as follows.

WSO2 DAS 3.0.0 architecture

Data that needs to be monitored goes through these modules in order. The data flow is as follows:

Data will be sent from event adapters and the analytics REST API to the DAS server.
Received data will be stored through the data layer in the underlying data store (RDBMS or HBase).
A background indexing process fetches the data from the data store, and does the indexing operations.
Analyzer engine, which is powered by Apache Spark will analyze this data according to defined analytic queries. This will usually follow a pattern of retrieving data from the data store, performing a data operation such as an addition, and storing data back in a data store.
The dashboard will query the data store for the analyzed data and will display them graphically.