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Gesamtkatalog

Catalogue complet

Provides a clear learning path for developers who want to start working with GraphQL, the revolutionary technology for data fetching.

Porcello Eve: Learning GraphQL

Learning GraphQL

Declarative Data Fetching for Modern Web Apps

Python in Excel Step by Step

To write effective code and applications, software engineers and developers have to be able to frame user/customer needs effectively, capture program requirements and use cases, and then develop suitable software architecture and code to meet the need. Code Chronicles: The Art of Storytelling in Software helps readers write better software by teaching readers how to write stories in the context of software development. The book explains the roots of storytelling, clarifies that storytelling historically has been a very powerful tool used to pass along knowledge, presents where storytelling is already present implicitly in software development, discusses how to make it more effective, and finally present experiences in storytelling from software engineering and other scientific disciplines, to foster a full understanding of its power. The authors comprehensively present the pivotal role of storytelling in writing software, and they explain how to do it in a simple, hands-on approach, also taking advantage of clear case studies written by experts in the field.

The Art of Storytelling in Software

Code Chronicles

There is an increasing prevalence of large and complex datasets within the social sciences, and notably criminology in recent years. This data explosion has led to the development of specialized techniques for extracting information from such data. This book presents an introduction to "Big Data Science" for criminology and the social sciences, taking a case study-based approach to explaining the concepts. The theory is introduced as needed to answer scientific questions based on real data problems in the application areas. Some R and Python code is included to give support with implementation of the methods.

From Case Studies to Theory

Big Data Science for Criminology and the Social Sciences

Building and Deploying AI Applications at Scale

ML and Generative AI in the Data Lakehouse

"International Perspectives on Science, Culture and Society"

The book addresses new challenges to garbage collection made by recent advances in hardware and software. It explores the consequences of these changes for designers and implementers of high performance garbage collectors

The Art of Automatic Memory Management

The Garbage Collection Handbook

Calculus for the Curious

Data is critical to ensuring the success of any business. A strong data governance programme can help any organization ensure that its data is high-quality, secure and accessible.

Effective Data Governance is a step-by-step guide for mid to senior data professionals to design a simplified data governance programme that meet the needs of their organization. Covering all of the processes, roles, standards and metrics to ensure the effective and efficient use of data within an organization, data governance is essential for every business. Beginning with an explanation of the importance of data governance and its challenges, this book covers how to plan your data governance approach, build a data governance framework and write a tailored data governance policy.

This book also describes how to setup and identify the key roles and responsibilities connected to data in an organization. It shows you how to identify the right process, resolve data quality issues, manage data risk and controls and track your progress. With real-world examples on how to implement the right type of data governance programme, this actionable guide is the key to the successful use of data.

Design a Framework that Works for Your Organization

Effective Data Governance

Chapman & Hall/CRC Computational Science

This book is a well-recognized and leading guidebook on High Performance Computing for a broad audience of readers from industry and academia. The new edition is completely reorganized and updated to include the latest research in HPC. A new introductory chapter and a new chapter on accelerated computing have been added to the book to keep pace with recent advances.

Introduction to High Performance Computing for Scientists and Engineers, Second Edition

Data Governance: How to Design, Deploy, and Sustain an Effective Data Governance Program, Third Edition, is for any student, executive, manager, or data professional who needs to understand and implement a data governance program, to ensure consistent, accurate and reliable data across their organization. The problem of managing data continues to grow with issues surrounding the cost of storage, exponential growth, as well as administrative, management, and security concerns - the solution to being able to scale all of these issues up is data governance which provides better services to users and saves money. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. John Ladley guides readers though the detailed process of developing a Data Governance program, including an introduction to the concepts and principles of Data Governance, Data literacy concepts, business case, strategy, systems architecture and design, the importance of team engagement, implementation, and change management. The Third Edition includes all-new coverage embracing new data capabilities such as ethics and AI integration, as well as key regulatory changes. Data governance is now inevitable, and no longer an option. John Ladley examines the impact of society on data and the relevance for organizations to simply "do better." The Third Edition updates coverage on data governance tools to achieve delivery of necessary capabilities. This valuable resource provides foundational understanding to advanced students in Data Management and related courses, as well as comprehensive guidance for beginning professionals, managers or analysts looking to improve their processes. With the provided framework and case studies, all students and professionals in the data governance field will gain key insights into launching successful and money-saving data governance programs.

How to Design, Deploy, and Sustain an Effective Data Governance Program

Data Governance

Application of Python in Healthcare Technology: Medical Data Analysis and Developing ML/AI Models provides comprehensive coverage of the Python programming language from a medical-based perspective. With a strong focus on utility-based learning rather than technical-based learning of Python, this title clarifies how the application of Python in the healthcare technology industry has a meaningful impact on patient care through the development of deep learning models for early prediction of diseases and the development of Clinical Decision Support System (CDS). In 13 chapters, an extensive range of topics pertaining to the intersection of Python and medical sciences is covered. Coverage defines how to set up an environment to work with python, describes Python class, methods, and functions, explains both basic and advanced statistical analysis in Python, and provides a tool to assist in the development of deep learning models such as API, Git, Github, NumPy, Pandas, and SciPy.

Medical Data Analysis and Developing ML/AI Models

Application of Python in the Healthcare Technology

Analytics Science to Improve the World

Insight-Driven Problem Solving

Learning GraphQL

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