This includes connecting to data sources and target systems as well as identifying the transformations needed to be performed on the raw data.ĭue to data being stored in multiple formats, structures, and data stores, a well-defined data integration architecture helps to capture, aggregate, cleanse, normalize, synthesize, and store the data in a form useful for processing. Without further ado, let’s jump right into it! Table of Contentsĭata integration architecture is a framework for designing and orchestrating a smooth flow between IT systems to form a single coherent view. To make this easier for you, we have prepared a comprehensive guide that takes you through the nitty gritty of an enterprise data integration architecture. A well-developed data integration architecture ensures smooth data flow between the source and destination locations by minimizing human intervention and automating the data collection and transformation process. Whether you need to see the ROI of your marketing campaigns or build a 360 customer profile, implementing the right data integration architecture allows you to form a single source of truth. Common Data Integration Architectural Patternsīy applying data integration concepts, you can effectively aggregate, clean & transform your complex raw data from various sources into meaningful insights.Data Integration Architecture Best Practices.Types of Data Integration Architectures. ![]() Importance of Data Integration Architecture.
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