Streaming Analytics

 Analysis of real-time, in motion data.

Data in motion

Streaming analytics platforms can ingest, analyse, and act on real-time streaming data coming from various sources so you can take immediate action while the events are still happening. It has the ability to gather and analyse large volumes of data arriving in “streams” from always-on sources such as sensor data, telematics data, machine logs, social media feed, change data capture data from traditional and relationship databases, location data, and so on.

How-to-Secure-Data-in-Motion-1
spacers

Streaming analytics vs traditional data analysis

The difference between streaming analytics and traditional analytics lies in the moment when data gets analysed. Traditional analytics first stores the data and then analyse sit for deriving insights. Traditional analytics is also mainly applied to data at rest.

In streaming analytics, we analyse the data first, while the events are still happening, and then store the relevant data for batch analysis. This allows streaming analytics platforms to handle the scale and constant flow of information and deliver continuous insights to users across the organisation.

Streaming Analytics vs traditional ENG