Advances in software and computing technologies have led to great efficiencies by automating and streamlining manual processes while amassing large volumes of data. Entity-relationship modeling, the database design technique often used in these applications, organizes data by reducing data redundancy in a manner called data normalization. While this technique works well for transactional applications, performance and functionality issues arise as these databases are accessed for reporting, analysis and decision-making purposes because entities have indexes to optimize data entry and processing as opposed to data extraction. Because redundancy is eliminated, multiple entities must be accessed to obtain the desired information. As the number of relationships increases, so does the complexity of those relationships, which also impacts performance. Functionality issues occur because data needed for reporting and analysis is often stored in disparate databases, thereby causing individuals to access multiple databases to obtain the data they need. These issues spawned the movement toward the creation of data structures and information repositories.
Data needed for reporting and analysis can be arranged and stored in numerous structures including data files, denormalized tables, OLAP/multidimensional cubes, operational data stores (ODSs), data marts and data warehouses (DWs). Each is vastly different, and each serves a specific purpose. Data files are typically provided to external parties requesting a set of detailed information or are used internally for analysis by another application. Denormalized tables are designed to contain redundant information and do not adhere to the rules of data normalization. They are often created as a quick solution to satisfying multiple reporting and analysis needs for the same set of data. Similar to a denormalized table, an OLAP cube contains highly redundant data. It also contains dimensions, which are used for trend or comparative analysis. ODSs, data marts and data warehouses are data structures that use relational database management systems. Through their database schema, they provide broader capabilities by containing both detailed and summarized data while providing extensive reporting and analysis possibilities. To create an organized and comprehensive information repository for your organization, an understanding of the role of each data structure is needed.
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