Large U.S. retail banks are building data warehouses and centralizing disconnected data marts. But warehouse-supported marts are proliferating, promising continued challenges to achieving a single enterprise customer view.
Despite widely reported disappointments, and some outright failures, of data warehouse initiatives, Gartner research shows that a data-warehouse-based architecture is the architecture of choice for customer information analysis and decision support among large U.S. retail banks. In a survey of U.S. retail banks with deposits of more than $1 billion, more than one-half of those with deposits of more than $4 billion said they use a data warehouse or data warehouse with associated data marts, with the percentage even higher for the very largest banks. In our research, the smaller banks (deposits between $1 billion and $4 billion) were more likely to say they use a series of unlinked data marts or rely on an operational customer information file (CIF) for analysis and decision support
Despite widely reported disappointments, and some outright failures, of data warehouse initiatives, Gartner research shows that a data-warehouse-based architecture is the architecture of choice for customer information analysis and decision support among large U.S. retail banks. In a survey of U.S. retail banks with deposits of more than $1 billion, more than one-half of those with deposits of more than $4 billion said they use a data warehouse or data warehouse with associated data marts, with the percentage even higher for the very largest banks. In our research, the smaller banks (deposits between $1 billion and $4 billion) were more likely to say they use a series of unlinked data marts or rely on an operational customer information file (CIF) for analysis and decision support
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