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Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Nowadays, knowledge-based management systems include data warehouses as their core components. The purpose of building a data warehouse is twofold. Firstly, to integrate multiple heterogeneous, autonomous, and distributed data sources within an enterprise. Secondly, to provide a platform for advanced, complex, and efficient data analysis. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed among others for discovering trends, patterns of behavior, and anomalies as well as for finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data that more and more often come from WEB-based, XML-based, spatio-temporal, object, and multimedia systems, make data integration and processing challenging. The objective of NEW TRENDS IN DATA WAREHOUSING AND DATA ANALYSIS is fourfold: First, to bring together the most recent research and practical achievements in the DW and OLAP technologies. Second, to open and discuss new, just emerging areas of further development. Third, to provide the up-to-date bibliography of published works and the resource of research achievements for anyone interested in up-to-date data warehouse issues. And, finally, to assist in the dissemination of knowledge in the field of advanced DW and OLAP. Stanislaw Kozielski works as a professor at the Silesian University of Technology, Poland. In 1977 he earned his Ph.D. in computer science (model building for information systems). In 1988 he received the D.Sc. in computer science (database design), and in 1997 he received the professor title in computer science. Between 1971-1991 and 2002-2007 he took part in several research, academic and industrial projects on software tools design, databases, information systems design, and information technologies. Between 1991-1996 he was the vice-dean and in 1996-2002 he was the dean of the Faculty of Automatic Control, Electronics and Computer Science of the Silesian University of Technology. His main research areas encompass databases (design, query languages), data warehouse technologies (efficiency, multidimensional modeling), and distributed processing (database query). Dr. hab. Robert Wrembel is an Assistant Professor in the Institute of Computing Science at Poznan University of Technology, Poland. In 2008 he received the post-doctoral degree in computer science, specializing in database systems and data warehouses. He was elected a deputy dean of the Faculty of Computing Science and Management for the period Sept. 2008 - Aug. 2011. Since 1996 he has been actively involved in five research projects on databases and four industrial projects in the field of information technologies. He has paid a number of visits to research and education centers, including INRIA Paris-Rocquencourt (France), the Paris Dauphine University (France), Klagenfurt University (Austria), and Loyola University (USA). His main research interests encompass data warehouse technologies (temporal, multiversion, object-relational) and object-oriented systems (views, data access optimization, methods and views materialization).

data warehousing --- gegevensanalyse

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Predict the future! This practical guide will help you use Big Data and technology to discover real-world insights, define projects, and help you create goals.

Digitale communicatie --- Management --- Data mining. --- Data processing. --- Mathematical models.

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Innovatie ; ondernemingen --- Data processing --- Bedrijfsbeleid

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Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done.

R (Computer program language) --- Statistics --- Data processing.

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Although Europe has a significant legal data protection framework, built up around EU Directive 95/46/EC and the Charter of Fundamental Rights, the question of whether data protection and its legal framework are 'in good health' is increasingly being posed. Advanced technologies raise fundamental issues regarding key concepts of data protection. Falling storage prices, increasing chips performance, the fact that technology is becoming increasingly embedded and ubiquitous, the convergence of technologies and other technological developments are broadening the scope and possibilities of applications rapidly. Society however, is also changing, affecting the privacy and data protection landscape. The 'demand' for free services, security, convenience, governance, etc, changes the mindsets of all the stakeholders involved. Privacy is being proclaimed dead or at least worthy of dying by the captains of industry; governments and policy makers are having to manoeuvre between competing and incompatible aims; and citizens and customers are considered to be indifferent. In the year in which the plans for the revision of the Data Protection Directive will be revealed, the current volume brings together a number of chapters highlighting issues, describing and discussing practices, and offering conceptual analysis of core concepts within the domain of privacy and data protection. The book's first part focuses on surveillance, profiling and prediction; the second on regulation, enforcement, and security; and the third on some of the fundamental concepts in the area of privacy and data protection. Reading the various chapters it appears that the 'patient' needs to be cured of quite some weak spots, illnesses and malformations. European data protection is at a turning point and the new challenges are not only accentuating the existing flaws and the anticipated difficulties, but also, more positively, the merits and the need for strong and accurate data protection practices and rules in Europe, and elsewhere.

Computer. Automation --- recht --- filosofie --- computercriminaliteit --- Engineering sciences. Technology --- ingenieurswetenschappen --- Legal theory and methods. Philosophy of law --- Data protection --- -342.0858094 --- Uk3 --- Data governance --- Data regulation --- Personal data protection --- Protection, Data --- Electronic data processing --- Law and legislation --- -Data protection --- -Law and legislation --- -Law and legislation -