By Alejandro Vaisman, Visit Amazon's Esteban Zimányi Page, search results, Learn about Author Central, Esteban Zimányi,
With this textbook, Vaisman and Zimányi carry very good assurance of knowledge warehousing and company intelligence applied sciences starting from the main uncomplicated ideas to fresh findings and purposes. To this finish, their paintings is based into 3 components. half I describes “Fundamental thoughts” together with multi-dimensional types; conceptual and logical information warehouse layout and MDX and SQL/OLAP. for this reason, half II information “Implementation and Deployment,” together with actual info warehouse layout; facts extraction, transformation, and loading (ETL) and knowledge analytics. finally, half III covers “Advanced subject matters” equivalent to spatial facts warehouses; trajectory facts warehouses; semantic applied sciences in information warehouses and novel applied sciences like Map decrease, column-store databases and in-memory databases.
As a key attribute of the publication, lots of the subject matters are awarded and illustrated utilizing program instruments. in particular, a case learn in keeping with the well known Northwind database illustrates how the recommendations offered within the e-book may be carried out utilizing Microsoft research companies and Pentaho enterprise Analytics. All chapters are summarized utilizing assessment questions and workouts to help entire scholar studying. Supplemental fabric to aid teachers utilizing this e-book as a path textual content is accessible at http://cs.ulb.ac.be/DWSDIbook/, together with digital types of the figures, strategies to all workouts, and a suite of slides accompanying each one chapter.
Overall, scholars, practitioners and researchers alike will locate this ebook the main finished reference paintings on info warehouses, with key themes defined in a transparent and academic style.
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Additional info for Data Warehouse Systems: Design and Implementation
For example, the web is changing the way in which data warehouses are being designed, used, and exploited. For some data analysis tasks (like worldwide price evolution of some product), the data contained in a conventional data warehouse may not suﬃce. External data sources, like the web, can provide useful multidimensional information, although usually too volatile to be permanently stored. The semantic web aims at representing web content in a machine-processable way. The basic layer of the data representation for the semantic web recommended by the World Wide Web Consortium (W3C) is the Resource Description Framework (RDF), on top of which the Web Ontology Language (OWL) is based.
In our example, the generalization is disjoint, since a temporary employee cannot be a permanent one. 4 Logical Database Design In this section, we describe the most used logical data model for databases, that is, the relational model. We also study two well-known query languages for the relational model: the relational algebra and SQL. 1 The Relational Model Relational databases have been successfully used for several decades for storing information in many application domains. In spite of alternative database technologies that have appeared in the last decades, the relational model is still the most often used approach for storing persistent information, particularly the information that is crucial for the day-to-day operation of an organization.
5. The aim of this chapter is to provide the necessary knowledge to understand the remaining chapters in this book, making it self-contained. However, we do not intend to be comprehensive and refer the interested reader to the many textbooks on the subject. 1 Database Design Databases constitute the core component of today’s information systems. A database is a shared collection of logically related data, and a description of that data, designed to meet the information needs and support the activities of an organization.