Data streaming makes it easier to manage and make accessible large quantities of data, communication between different programs is improved, and users gain access to real-time information, which is becoming increasingly important.
Data is received, compiled and distributed via a message queue. It is then processed in real-time and stored, and new information is presented back to the source from which it came – or elsewhere. The data’s journey from start to finish takes place in what is known as a ‘data streaming pipeline’.
Many companies have over time built up a range of different systems, databases and servers that store their data. This makes it complicated to extract, compile and use the data. Data streaming makes this much easier, and the response time goes from slow to taking place in real-time. Data streaming is being used increasingly in most industries. It is a technology that creates numerous new opportunities. Example applications include:
1. Banks can use the power of real-time data to calculate and grant loans, to prevent money laundering and to carry out risk analysis.
2. Insurance companies can identify the products a customer has and determine how big a pay-out a customer should receive.
3. The health service compiles data from various patient monitoring instruments and identifies the future course of diseases in patients.
4. The Norwegian Labour and Welfare Administration keeps track of all the events that take place in the life of Norwegian citizens.
5. Uber shows you where the car you have requested is in real-time, and adjusts its prices automatically on the basis of supply and demand.
6. Online shops provide you with recommendations on the basis of your previous purchases and what you are buying now.
A data streaming platform is an efficient way of making data from various sources easier to manage and more accessible.