دانلود کتاب طراحی و پیاده سازی سیستم های انبار داده

Since the late 1970s, relational database technology has been adopted by most organizations to store their essential data. However, nowadays, the needs of these organizations are not the same as they used to be. On the one hand, increasing market dynamics and competitiveness led to the need to have the right information at the right time. Managers need to be properly informed in order to take appropriate decisions to keep up with business successfully. On the other hand, data held by organizations are usually scattered among different systems, each one devised for a particular kind of business activity. Further, these systems may also be distributed geographically in different branches of the organization. Traditional database systems are not well suited for these new requirements, since they were devised to support day-to-day operations rather than for data analysis and decision making. As a consequence, new database technologies for these specific tasks emerged in the 1990s, namely, data warehousing and online analytical processing (OLAP), which involve architectures, algorithms, tools, and techniques for bringing together data from heterogeneous information sources into a single repository suited for analysis. In this repository, called a data warehouse, data are accumulated over a period of time for the purpose of analyzing their evolution and discovering strategic information such as trends, correlations, and the like. Data warehousing is a well-established and mature technology used by organizations to improve their operations and better achieve their objectives.