Common technical and business problems with data streams
The implementation of an architecture capable of managing data streams is a complex project because data is continuously generated from a large variety of sources (IoT sensors and devices, IT systems, websites, social networks). These sources dispense data using many different types of formats. Among the technical problems that can slow down data streaming projects there are some main ones:
Errors caused by duplication, anomalies, data inconsistency
For example, the data acquired by IoT sensors can often be ‘dirty’, and contain ‘out of range’ readings, null or duplicate values, syntax errors, which require cleaning.
Problems of non-homogeneity of data present in different systems
The fragmentation of data across multiple business systems creates standardization difficulties. Even applications, produced by different manufacturers, could operate using different schemes and data structures, which end up corrupting the data pipeline.
Disaster recovery challenges
In case of catastrophic events, it is necessary to organize a disaster recovery plan to restore the functioning of the data streaming application, typically implemented on server clusters, which can be distributed across multiple data centers.
Architectural approaches for data streams
Mia-Platform offers a Fast Data solution that allows you to create a data streaming platform capable of anticipating or solving the technical problems just mentioned, by applying, for example, rollback mechanisms and management strategies aimed at ensuring that data is always clean and consistent throughout the system.
Mia-Platform solution allows decoupling contact channels from IT systems, through a digital layer, composed of different services, which acts as a Digital Integration Hub.
The data flows into a stream and is immediately aggregated into JSON Single Customer Views (SCV) by a series of specially created microservices. Consequently, SCVs are exposed to various applications and channels.
Channels can call APIs to access unique views, or receive a push notification for changes, following the CQRS (command query responsibility segregation) architectural approach.
The data is saved on a high-performance, low-latency database, which always keeps the information updated and accessible to the channels, regardless of the availability of the underlying systems. All the operations on the channels involving the IT systems are mediated and performed asynchronously.
A stream of constantly updated data and a single view of all customer information allow us to provide timely, accurate, and valid answers to customer needs. Choose Mia-Platform Fast Data to build your data streaming platform and unlock the real value of your data.