Analysis of the Use, Importance, and Implementation of a Data Dictionary

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Analysis of the Use, Importance and Implementation of A Data Dictionary Introduction Data dictionaries have evolved into one of the most transformational and valuable components of databases architectures given the increasingly complex integration, data analysis and data management tasks enterprises need to accomplish. The use, importance and implementation of data dictionaries are analyzed and explored with specific focus on their use in enterprises who have intensive information and intelligence management needs daily. Analyzing the Uses of of Data Dictionaries The data dictionary has evolved from being a repository of fundamental database attributes, data models and definitions of elements, files, records, users to a critical framework component for enabling application, data and system integration (Stonebraker, 2010). Data dictionaries have evolved to fill the need enterprises have for unifying and integrating diverse, often previously siloed databases and legacy systems together, creating more agile, advanced and comprehensive data models that define a business' entire value chain (Asscher, 1984). Integrating customer and sales data across the enterprise has led to Customer Relationship Management (CRM) systems becoming more effective in attracting, selling and serving prospects and customers both. At a system architectural level, the data dictionary acts as the catalyst of Master Data Management (MDM) integration which integrates siloed, legacy systems to make
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