real time streaming data

Flink: Time Windows based on Processing Time

Reading Time: 4 minutes In the previous blog, we talked about Flink’s windows operator, a heart of processing infinite streams. Generally in Flink, after specifying that the stream is keyed or non keyed, the next step is to define a window assigner. The window assigner defines how elements are assigned to windows. Flink provides some useful predefined window assigners like Tumbling windows, Sliding windows, Session windows, Count windows, and Continue Reading

real time analytics in banking

Banking on Real-Time Analytics for Better Customer Experience

Reading Time: 4 minutes The digital storm has now made its presence felt across various industries and the banking and financial sector is also not far behind. The way customers interact with banks is not the same anymore. Things have become “in-the-moment” and banks need to be responsive as things get up to speed. Customers have become so used to mobile and online banking, that it’s taken for granted Continue Reading

Fast Data: The New Age Analytics For Enhanced Customer Experience

Reading Time: 6 minutes Data is evolving both in terms of quality and quantity in today’s enterprises and in the past few years, changes have occurred at a much faster pace. Not long ago, Big Data was considered the next big thing for digital transformation. Technologies like Hadoop and HBase made sense as batch processing of data was the norm. But things are not the same now.  By the Continue Reading

RealTimeProcessing of Data using kafka and Spark

Reading Time: 3 minutes Before Starting it you should know about kafka, spark and what is Real time processing of Data.so let’s do some brief introduction about it. Real Time Processing – Processing the Data that appears to take place instead of storing the data and then processing it or processing the data that stored somewhere else. Kafka – Kafka is the maximum throughput of data from one end to another . Continue Reading