A framework for polyglot information integration that allows for the smooth integration of diverse data types and sources
Keywords:
Data Integration, Heterogeneous Data Sources, Data Framework, Data MappingAbstract
Businesses that want to fully use the value of their data must effectively manage and combine these many types. This is the situation where a polyglot data integration architecture fits. This framework seeks to provide a flexible and scalable solution able to control many data sources and formats while keeping performance and consistency. Using advanced technologies like cloud-based storage, APIs, and machine learning ensures flawless data system interface within the framework. It helps companies to combine their data so that integrity and quality across all platforms are maintained. Moreover, the structure tackles the scalability problem thereby enabling companies to control growing data volumes free from delays or disruptions. This approach helps companies improve their data operations thereby simplifying the data integration process and reducing mistakes. This improves decision-making capacity as companies depending on a homogeneous and consistent view of their data may depend on it independent of the source or format.
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