San Francisco, 21 February 2017. During the WSO2 conference USA 2017, where Yenlo as premier partner of WSO2 is one of the silver sponsors, Sriskandarajah Suhothayan from WSO2 was talking about the WSO2 Data Analytics Server and the future roadmap. Read all about it in this post.
Being unaware of things happening around you will make you blind for imminent disasters from happening and for opportunities available to you. This is true for your as a person as well as the technology stack facilitating your business.
To keep track of matters in your technology stack you can use analytics tooling to provide you with insight. Using events to signal about things happening inside your IT platform you gain insight into potential new business ideas, new revenue stream but also in bottlenecks in your data-flows or user processes and issues within the data-handling you are executing.
WSO2 Data Analytics is a solution which enables you to get insight in both your technology stack as well as the data flowing through it.
The presentation given by Sriskandarajah Suhothayan at WSO2Con 2017 was all about explaining the WSO2 Data Analytics Server capabilities and in what ways you can analyze your data to provide your with very valuable insight. For instance, how to go about detecting fraud in transactions and how to get insight in your (car-)fleet. Insight in fuel-consumption and real-time insight in location of the vehicles in the fleet.
Using various connectors you can get data into the DAS and provide other systems with analyzed data generated within the DAS. There is a broad set of connectors available on the Analytics extension store which you can find on http://store.wso2.com
WSO2 DAS can perform streaming analytics on data coming into the DAS real-time through any of its connectors. Using a language named Siddhi analytics-models can be implemented to get the insight from all events which are coming into the DAS. You can analyze in batch, in real-time, using temporal data and in a combined mode where you can use both batch-analyzed data together with real-time data.
Using the machine learner capability, you can also feed seemingly unrelated data into the DAS and use various methods to make sense out of seemingly unrelated data.
A key differentiator for WSO2 DAS is its capability to do real-time analytics. Being able to combine both batch-analyzed data together with real-time (incoming) data provides you with the valuable information which your digitally transforming enterprise needs.
If you are looking insight in your data or technology stack then give WSO2 DAS a spin and try out its rich capabilities.