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The practice of data management and integration (DMI) refers to the application of certain types of data management in order to promote the best use of information and maintenance throughout the data life cycle. IT professionals use these kinds of tools and philosophies to optimize the IT setups for businesses.
In general, data management refers to all of the various things that enterprises do to manage data through their entire life cycle. Aspects of data management include data integration, data governance and data quality efforts. For example, in data governance, policy-driven standards for data help to make sure that they are correctly formatted for use in a business system.
Data integration is different; experts define data integration as combining data from multiple sources and presenting them in a unified way. Data integration can be thought of as breaking down "information silos" wherein certain kinds of data are isolated within an IT architecture and cannot be used correctly. One central idea in data integration is to create a centralized data warehouse, which is a repository for all of the different kinds of data from multiple sources. Software applications called middleware drive the data from those aggregate sources into the central data warehouse, where they are curated and stored for future use. Data management and integration efforts look at how to handle data well and apply them in the best ways to promote business goals and objectives.