Mining Very Large Databases with Parallel Processing addresses the problem of large-
scale data mining. It is an interdisciplinary text, describing advances in the integration of …

This book is the result of a study path that started in 2006, when the two authors of this book
published the book Data Quality: Concepts, Methodologies and Techniques. After 8 years …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

Abstract The Grammar of Graphics, or GOG, denotes a system with seven orthogonal
components. By orthogonal, we mean there are seven graphical component sets whose …

The rapid growth of the Web in the past two decades has made it the largest publicly
accessible data source in the world. Web mining aims to discover useful information or …

Data warehousing systems enable enterprise managers to acquire and integrate information
from heterogeneous sources and to query very large databases efficiently. Building a data …

Analysts predominantly use OLAP data cubes to identify regions of anomalies that may
represent problem areas or new opportunities. The current OLAP systems support …

Medical informatics has been an important area for the application of computing and
database technology for at least four decades. This area may benefit from the functionality …

RasDaMan is a universal—ie, domain-independent—array DBMS for multidimensional
arrays of arbitrary size and structure. A declarative, SQL-based array query language offers …

Data warehouses are databases devoted to analytical processing. They are used to support
decision-making activities in most modern business settings, when complex data sets have …