Integration with Legacy Systems
Posted: Tue Feb 11, 2025 7:07 am
Integrating streaming data with existing legacy systems is another significant technical challenge. Many organizations have invested heavily in their existing data infrastructure, with a mix of relational databases, data warehouses and batch-processing systems. Integrating these legacy systems with streaming data platforms requires building custom connectors, handling schema evolution and ensuring data consistency and compatibility across different systems. This can be a complex and time-consuming process, requiring significant engineering effort and expertise.
To streamline the integration process, companies can leverage pre-built connectors and integration frameworks, which provide a pluggable architecture for connecting various data sources and sinks to brazil whatsapp number data streaming data platforms. Any platform with a schema registry will help ensure data compatibility and seamless schema evolution, reducing the complexity of managing data contracts between different systems.
Data Security and Compliance Concerns
Data security and compliance are critical technical concerns for companies considering the adoption of streaming data. Enforcing controls like role-based access control policies on streaming data adds an additional wrinkle to the data management process.
To streamline the integration process, companies can leverage pre-built connectors and integration frameworks, which provide a pluggable architecture for connecting various data sources and sinks to brazil whatsapp number data streaming data platforms. Any platform with a schema registry will help ensure data compatibility and seamless schema evolution, reducing the complexity of managing data contracts between different systems.
Data Security and Compliance Concerns
Data security and compliance are critical technical concerns for companies considering the adoption of streaming data. Enforcing controls like role-based access control policies on streaming data adds an additional wrinkle to the data management process.