With nearly every business across the globe relying on collecting and responding to data, event streaming is more important than ever to the global economy.
While few people outside of IT or other technology-based disciplines have heard of event streaming, it’s currently used across more industries than ever before. But what is event streaming?
Put simply, event streaming is a data processing method in which incoming data about an event is analysed and responded to in real-time.
As an example, let’s say a customer places an order with an eCommerce business, which would be the “event”. This method of streaming allows the company’s database to immediately take action on that data, process the order, send a confirmation email, and deliver that order data into the company’s fulfilment software.
Before event streaming, legacy data processing methods used batch processing. Using this method, data must be collected in a batch before it can be processed. Batch processing has its merits, but it wouldn’t be able to support applications that need data to be streamed and processed in real-time.
Using the example above, this would mean that the eCommerce business’ databanks might only process orders, analyse the order data, and create a response once a set interval has passed. This could be a set period of time, like an hour, or a set number of incoming orders.
Batch processing has a major disadvantage against real-time event streaming in that it can’t support modern data requirements. With most large, modern organisations collecting millions of data points every second, batch processing can present a roadblock against the smooth operation of company processes.
However, batch processing is an extremely efficient method of processing large amounts of data that don’t need to be acted on in real-time. It’s for this reason that it’s commonly used for line item invoicing, payroll processing, and certain financial transactions.
Event streaming platforms are a central hub for real-time event streaming, which makes it easier for businesses to read and understand all incoming data and how it moves through each pipeline (the set of processing steps that enable the flow of data from a source to a destination). An enterprise event streaming platform will help reduce operational complexity while ensuring high performance and scalability as event streaming grows through the organisation. By integrating data from disparate IT systems into a single streaming platform, the business can process and act on the massive amounts of data that arrive, as they arrive.
An event-streaming platform can also be used to detect patterns and query data that comes through a real-time event streaming pipeline. This software allows users to complete data searches across multiple forms of input data, time frames, and different search terms without needing to build application-specific software that can complete the search.
For businesses that need to cross-reference old event data alongside incoming information, such as investors and finance professionals who need to keep track of stock markets, event streaming platforms can complete pull requests to fetch previous event data. They also allow for old event streams to be re-run through the platform, giving businesses and professionals greater analytic power when testing new algorithms.
A familiar example of event streaming is Uber’s app. When a customer requests a ride through Uber, the app will collect real-time traffic data and a driver’s location to show users a map and the estimated time that the driver will arrive. The app will also constantly gather traffic data to push updates to the customer and show a real-time map of where the driver is.
This combined tracking of traffic data along with GPS locations is becoming more widely used across other ride-sharing platforms and taxi services for good reason. By giving customers an updated map to show where drivers are, the number of calls to operators are reduced.
Event streaming is also widely used in the financial industry to alert businesses and professionals of significant stock price changes, allowing them to make better investment decisions in real-time.
Another great example of event streaming is the real-time information on available stock we observe on eCommerce sites. By showing a customer how much stock is available, it’s easier for them to make a purchasing decision. Once they make a purchase, real-time event streaming will not only send that data to the purchase pipeline, but it will also update the website’s stock levels and the warehouse inventory database to reflect the change.
If you would like to find out how to become a data-driven organisation with event streaming, Kafka and Confluent, then give us a call or email us at Salesforce@coforge.com
Other useful links:
What is Kafka? The Top 5 things you should know