In recent years information has steadily increased in importance for modern day companies and data-warehousing has been described by many as the highest priority post-millennium IT project. As progressive companies are complex and deal with and in fast changing environments, oftentimes with a rapidly growing database, questions regarding current data designs and approaches arise. Can technologies developed in the 1960s support today's and future demands? Author Sascha Mendack gives an introduction to the associative model of data and how it could fulfil the future requirements of modern data-warehousing and reporting. He analyses the data model using the FASMI test by Nigel Pendse and compares its advantages and disadvantages with the well known multidimensional data model. Following up the theoretical review he reviews an OLAP application that uses the new data model. This book is intended for everybody who is interested in an introduction of the associative data model and is looking for new alternatives and approaches in the field of OLAP.
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In recent years information has steadily increased in importance for modern day companies and data-warehousing has been described by many as the highest priority post-millennium IT project. As progressive companies are complex and deal with and in fast changing environments, oftentimes with a rapidly growing database, questions regarding current data designs and approaches arise. Can technologies developed in the 1960s support today's and future demands? Author Sascha Mendack gives an introduction to the associative model of data and how it could fulfil the future requirements of modern data-warehousing and reporting. He analyses the data model using the FASMI test by Nigel Pendse and compares its advantages and disadvantages with the well known multidimensional data model. Following up the theoretical review he reviews an OLAP application that uses the new data model. This book is intended for everybody who is interested in an introduction of the associative data model and is looking for new alternatives and approaches in the field of OLAP.
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