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This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Data Management in Grids, DMG 2005, held in Trondheim, Norway in September 2005 in conjunction with VLDB 2005. The 9 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 24 submissions for inclusion in the book. The papers address all current research activities in relation to data management in dynamic, heterogeneous and cross-organizational environments, i.e. grids. They show unique expertise in the management of very large, widely distributed databases. Conversely, Grids offer a novel and very exciting field of research for database scientists both in terms of application domains and fundamental research.

This book constitutes the refereed proceedings of the 19th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2017, held in Moscow, Russia, in October 2017. The 16 revised full papers presented together with three invited papers were carefully reviewed and selected from 75 submissions. The papers are organized in the following topical sections: data analytics; next generation genomic sequencing: challenges and solutions; novel approaches to analyzing and classifying of various astronomical entities and events; ontology population in data intensive domains; heterogeneous data integration issues; data curation and data provenance support; and temporal summaries generation.

Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications.  It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it.  This third edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, this edition includes: ·         A new chapter on the analysis of mediation and moderation effects ·         Examples using STATA for most of the statistical methods ·         Example of XLSTAT applications Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods particularly relevant and typically used in management research, and to learn how they can be applied using widely available statistical software.

This book constitutes the thoroughly refereed proceedings of the 6th International Conference on Data Management Technologies and Applications, DATA 2017, held in Madrid, Spain, in July 2017. The 13 revised full papers were carefully reviewed and selected from 66 submissions. The papers deal with the following topics: databases, big data, data mining, data management, data security, and other aspects of information systems and technology involving advanced applications of data.

This book constitutes the refereed proceedings of the 7th International Conference on Information Management and Big Data, SIMBig 2020, held in Lima, Peru, in October 2020.* The 32 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 122 submissions. The papers address topics such as natural language processing and text mining; machine learning; image processing; social networks; data-driven software engineering; graph mining; and Semantic Web, repositories, and visualization. *The conference was held virtually.

Private wealth management (PWM) involves the management of the assets of high net worth individuals (HNWI) or accredited investors. Private wealth management firms have established close working relationships with high net worth clients to understand their financial needs and help them build investment portfolios that can meet their clients' financial goals.

Private wealth management (PWM) involves the management of the assets of high net worth individuals (HNWI) or accredited investors. Private wealth management firms have established close working relationships with high net worth clients to understand their financial needs and help them build investment portfolios that can meet their clients' financial goals. They offer a range of services, including portfolio management, real estate planning, mortgage planning, asset protection, tax management, and other financial services. Private wealth management services are provided by large corporations, independent financial advisers and portfolio managers who specialize in working with high net worth private clients.

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