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The modern world is defined by speed. Grocery delivery, rideshare apps, and payments for just about anything can happen instantly using a mobile device and its apps. Every action of every consumer creates data, and businesses must make sense of it quickly to take advantage in real time.
The modern world is defined by speed. Grocery delivery, rideshare apps, and payments for just about anything can happen instantly using a mobile device and its apps. Every action of every consumer creates data, and businesses must make sense of it quickly to take advantage of opportunities in real time.
This is where real-time data streaming comes in. Older batch processing lets users submit lots of data to be processed in a certain period of time, but it can take days or even weeks. Real-time data streaming emerged alongside new sources of dynamic data, like traffic maps and store inventory levels. If you’ve tracked a grocery order or anticipated your ride-sharing service down to the minute, you’ve experienced real-time service.
And real-time service is essential for businesses these days, especially in industries like retail or travel. A recent Lawless Research survey of 1,950 IT and engineering leaders found that 3 in 4 organizations would lose customers without the insights they get from real-time data, with retailers most likely to suffer.
The survey also found that real-time data streaming takes some work: 60% of IT leaders say difficulties integrating multiple sources is the top hurdle to accessing more real-time data.
Data streaming platforms like Confluent use real-time pipelines to collect, store, and use data continuously using event-driven principles. Each change in the data, known as an event, triggers new data to be received and integrated into the processing function.
Download this free infographic and learn more about the fundamentals of data streaming.