Capturing web-click streams by ecommerce sites to identify browsing patterns of prospective customers and send promotion campaigns that are pinpointed to their needs based on this data streams.Processing these will be helpful in identifying slow moving traffic, bottlenecks and locations where additional servers are required to ease or handle the traffic. In the IT sector, several network or mail servers of data centres keep generating logs.Purchase behaviour from the above type of data streams can also be used by retail industry to push attractive sales/discount campaigns to clients as part of their up-selling or cross-selling promotions.
In the banking/financial services domain, monitoring credit card transactions that keep streaming in continuously from various sources like transactions at points-of-sale, ecommerce sites and mobile apps to detect and flag credit card frauds.Processing streaming data has become very important and essential. In an organization, we would have a number of data sources that generate a variety of streaming data at high velocity and high volume.
It can be used to transport large volumes data streams from any possible data source. The application of Apache Flume is restricted not only to log data aggregation. Apache Flume, as its website mentions – is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store such as Hadoop HDFS.
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