Big data & analytics bring together open source technologies. That works together to accelerate the data pipeline. They are : Spark - for large-scale data processing

Mesos -  for cluster resource management

Akka - for data-heavy applications

Cassandra - for storage engine and 

Kafka - for event processing

To gain the full value of data, there is a need to analyze it in real time. Read more at:  http://www.cio.com/article/3068672/analytics/igniting-faster-analytics-with-the-smack-stack.html

Inspite of the fact that Big Data analytics is found everywhere, the willingness of the firms to invest and to act on analytics insight is extremely slow. This is decision latency, where the companies have all the required data and knowledge but lacks the speed to make decisions on major issues. In today's world, data becomes less relevant with each passing minute. Traditional analytics tools face challenges in handling this data because they are designed to store and process the data but not to analyze this data from moment to moment. Three capabilities crucial for event processing systems to deliver ROI, are as follows :

1. High availability
2. User empowerment
3.  Empowerment of developers in order to built better distributed system with custom UIs (User Interface).

Read more at http://www.tibco.com/blog/2015/06/09/decision-latency-solving-the-big-data-analytics-oversight/