Why Should Businesses Utilise Real-Time Data Streams?
Author: Jamie Turbill
Release Date: 25/07/2024
Increasingly and in the last decade, data has become one of the most important assets in business. As services become ever more digital, we expect things to be available on-demand in an instant. Organisations are reliant on data-driven systems to provide these services and if they go wrong, it can result in considerable reputational and/or financial impact.
Traditionally, when the number of services was small, it was possible to get by - by using batch processing or setting up bespoke point-to-point integrations.
Batch processing processes chunks of data over a larger time range - e.g a daily cron job. This works but the insights the data provides may already be out of date, and the window for getting value from the data may be quite small. For example, if you’re providing ecommerce services and want to react to a sudden price drop by a competitor for a popular product- by the time you process that data you might have already lost a lot of sales!
Sometimes, businesses might overcome this with a point-to-point integration, but due to the ever expanding number of services and tools that we all use and rely on this quickly becomes complex, and it can be very difficult to maintain. Data is often used and needed in several places - having point-to-point integrations for each place will cost a lot of time, and indeed money.
This is where real-time data streams come into play, allowing you to realise value from your data instantly and make faster, data-driven decisions to respond to changing conditions.
Confluent, with Kafka, have revolutionised how businesses manage and analyse data. By providing the central core for your data, it makes achieving and creating real time data streams reliably possible. There are many use cases for real-time data streams, some of which I’ve detailed below:
E-Commerce
Enhancing customer experience is an important part of ecommerce. If the platform is frustrating to use or doesn’t offer what’s expected, revenue is lost. Real-time data streams can allow for you to offer bespoke product recommendations, offer customers targeted promotions, or even react to pricing/market changes quickly.
Additionally, monitoring the e-commerce platform effectively to ensure it’s online and being able to proactively react to any possible issues is another benefit that real time data streams can provide for these platforms. Any downtime is money lost - so being able to spot and rectify issues before they manifest can reduce costs and reputational damage.
Airports
Airports have enabled us to explore and travel the world, but to do so they need to handle millions of passengers going to hundreds of destinations. They must handle huge quantities of data that often needs to be communicated between the airlines, ground services such as the luggage handlers and all the infrastructure in the terminal, such as the check in desks, the departures/arrivals boards, security/passport control, and the departure gates.
Being able to use and process real-time data streams can enable airports to reduce delays, keep passengers moving and make the most efficient use of their available, and often limited capacity. And when the unexpected does happen, passengers can be kept informed by providing an effective means for that data to reach all the relevant systems needed to get them from A to B.
IoT
IoT devices often contain a lot of crucial sensors that provide a range of information about the running of the device. IoT devices that exist in critical infrastructure, such as utility plants, medical facilities, transport and more must be robust enough to avoid any issues that in some cases, could cause significant damage or even injury.
Using real-time data streams to monitor these important sensors allows for real-time monitoring of critical components and being able to react quickly to any deteriorating conditions, by bringing standby infra online or modifying running configurations to avoid larger issues.
Logistics/Supply Chain
Getting products from A to B can be a complex challenge. Lots of factors can impact logistics/supply chain processes. Infrastructure issues, weather conditions, seasonal events are just some of these.
Real-time data streams can be used to monitor the progress of the supply chain from A to B, monitor critical infrastructure, such as vehicles used to transport goods, provide tracking updates to customers and more. The data provided from the supply chain could be used to reroute parcels for example in the event of a severe weather event, or can be used to note increasing demand from seasonal events, such as black friday or the holiday period.
Those are just some example use cases but we encounter data every day in our daily lives. There are of course many more examples out there. By implementing a solution like Confluent, you can make using data more effective for your business, enabling sometimes significant cost reductions, increased user experience and customer satisfaction, and new experiences.
