![]() ![]() When data is shared manually, obtaining knowledge for decision support becomes cumbersome and impacts customers and business performance.Ĭreating a data integration architecture allows integration of disparate data and provides normalization to enable faster decision support. This means users spend far more time searching for data and information instead of using it to make better business decisions. Today, data is everywhere, often stored in multiple formats in a complex non-integrated fashion. What is Data Integration Architecture?ĭata integration architecture defines the flow of data between IT assets and organizational processes to enable interoperability between systems. Organizations need a data integration architecture to connect secondary to primary data sources, normalize the information, and automate the flow of information without manual interventions. This can be a challenge when functional units use multiple applications and store data in multiple locations. In order to efficiently share data, businesses need to focus on integrating their data in an automated and timely manner. Similar to a professional sports team, each function in the organization should have a specific role, sharing data and information in real-time to support better outcomes. Usually, data does not belong to a specific group within an organization and is often shared across teams and applications. In any organization, you will find data in multiple applications, databases, data warehouses, and in many cases, public and private clouds. ![]()
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