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Data analysis for database design is a subject of practical value to systems analysts and designers. This third edition has been updated to ensure that developments concerning relational databases are included. In particular, there is a new section on the object-orientated approach and a detailed case study outlining the use of SQL in first and second level design. The book explains techniques from a practical standpoint by using small-scale realistic examples and "answer pointers" at the end of...

This book presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.

This book contains the proceedings of the 2018 International Conference on Data Science (ICDATA'18). ICDATA is the renamed former International Conference on Data Mining, DMIN, which was held for the past thirteen years. Therefore, we will continue with the 14th conference on this topic. We hope that the new name (and acronym) will be more attractive and reflect a more modern perspective – although the content itself has not changed dramatically in the sense, that we still aim at organizing an...

This book addresses computationally-efficient multi-objective optimization of antenna structures using variable-fidelity electromagnetic simulations, surrogate modeling techniques, and design space reduction methods. Based on contemporary research, it formulates multi-objective design tasks, highlights related challenges in the context of antenna design, and discusses solution approaches. Specific focus is on providing methodologies for handling computationally expensive simulation models of ant...

Over the past fifty years, preservation policy has evolved very little, despite escalating accusations that landmarking and historic districting can inhibit affordable housing, economic development, and socioeconomic diversity. The potential to understand these dynamics and effect positive change is hindered by a lack of data and evidence-based research to better understand these impacts. One of the biggest barriers to preservation research has been the lack of data sets that can be used for geo...

See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. Yo...

The only modern data structures book implemented in Ada, covers data structures first in terms of specifications, followed by implementation, then by performance issues. The organization moves from the more basic structures to the more advanced structures. The book contains examples coded in Ada and content specially tailored to the features and capabilities of the language. Examples throughout the text illustrate the use of data structures and exercises vary from straightforward paper and penci...

Design algorithms using pseudocode with the only practical and comprehensive text on C programming specifically designed for students.

This accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continua...

Save time analyzing volumes of data using best practices to extract, model, and create insights from your dataKey FeaturesMaster best practices in data modeling with Tableau Prep Builder and Tableau DesktopApply Tableau Server and Cloud to create and extend data modelsBuild organizational data models based on data and content governance best practicesBook DescriptionTableau is unlike most other BI platforms that have a single data modeling tool and enterprise data model (for example, LookML from...

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate t...

44301-0 Leverage HP OpenView's extraordinary power in telecommunications network management. HP OpenView is an extremely powerful network management platform, but many network management applications fail to leverage its full power. This book will help you develop robust telecommunications network management applications that leverage all of OpenView's capabilities, especially its support for CMIP and CMISE. Power Programming in HP OpenView first presents an overview of current network managemen...

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build r...

Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandasKey FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook DescriptionExploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse...

Offered as an introduction to the field of data structures andalgorithms, Open Data Structures covers the implementation andanalysis of data structures for sequences (lists), queues, priorityqueues, unordered dictionaries, ordered dictionaries, and graphs.Focusing on a mathematically rigorous approach that is fast, practical,and efficient, Morin clearly and briskly presents instruction alongwith source code.

This book constitutes the refereed proceedings of the 12th Latin American Symposium on Theoretical Informatics, LATIN 2016, held in Ensenada, Mexico, in April 2016.The 52 papers presented together with 5 abstracts were carefully reviewed and selected from 131 submissions. The papers address a variety of topics in theoretical computer science with a certain focus on algorithms (approximation, online, randomized, algorithmic game theory, etc.), analytic combinatorics and analysis of algorithms, au...