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Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithms and data structures : The Basic Toolbox
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language.
Adapting Proofs-as-Programs : The Curry--Howard Protocol
This book nuds new things to do with an old idea. The proofs-as-programs paradigm constitutes a set of approaches to developing programs from proofs in constructive logic. there is increasingly active research in applying constructive techniques to industrial-scale, complex software engineering problems. Thismonographdetailsseveralimportantadvancesinthisdirectionofpr- tical proofs-as-programs. One of the central themes of the book is a general, abstract framework for developing new systems of program synthesis by adapting proofs-as-programs to new contexts. Framework-oriented approaches that facilitate analogous - proaches to building systems for solving particular problems have been popular and successful. Thesemethodsarehelpful asthey providea formal toolbox that enablesa“roll-your-own”approachtodevelopingsolutions.Itishopedthatour framework will have a similar impact. The framework is demonstrated by example. We will give two novel - plications of proofs-as-programs to large-scale, coarse-grain software engine- ing problems: contractual imperative program synthesis and structured p- gram synthesis.
Management Methods and Tools : Practical Know-how for Students, Managers, and Consultants.
This textbook includes the most important management methods and tools. The author does not restrict himself to describing the scientific methods but also shows how to apply them to real-life situations. The management tools he introduces have been successfully tested during 20 years of experience. The various methods are described and analyzed in detail, and many examples illustrate their application. Thus, the textbook gives a fundamental and comprehensive insight into the practice of successful management. It is clearly structured and provides essential in-depth knowledge for students as well as for managers and consultants.
Knowledge Integration : The Practice of Knowledge Management in Small and Medium Enterprises
The ability to manage knowledge is relevant for millions of small and medium sized enterprises (SMEs) that operate in high-tech environments. They strongly depend on external knowledge about customers, technologies, and competitors because, as opposed to large companies, they have limited internal knowledge resources and little power to control their business environments.
Advanced robust and nonparametric methods in efficiency analysis : Methodology and applications
This readable book makes available an intuitive yet rigorous presentation of advanced nonparametric and robust methods. This flexible toolbox can be used in theories based on the neoclassical theory of production and its alternatives, including evolutionary theories.
Adaptive Information Systems and Modelling in Economics and Management Science
Learning and adaption are key features of "real economies". Studying interesting real phenomena like innovation, industry evolution or the role of expectation formulation in financial markets thus necessitates novel methods of data analysis and modelling. This title covers statistical models of heterogeneity, artificial consumer markets, models of adaptive expectation formulation in financial markets and agent-based models of industry evolution, product diversification and energy markets. The joint findings are presented in a manner that is interesting both for readers with a background in economics/management and mathematics and statistics and also for non-expert readers because it allows them to grasp the ideas of modern management science. This book thus provides a unique integrated toolbox for building realistic agent-based models of learning and adaption in a variety of settings based on sound data analysis.
