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Data-Directed Mathematical Modeling

Best Practices for Scaling and Optimizing Apache Spark

High Performance Spark

Use this step-by-step guide to prepare, design and implement a simplified data governance programme built to meet the needs of your organization. Prepare, design and implement a data governance framework that works for your organization with this practical guide to harnessing data successfully.

Design a Framework that Works for Your Organization

Effective Data Governance

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

The theory and practice of using TDM for scholarship in the humanities

Text and Data Mining

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains. It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Advanced Intelligence Methods for Data Science and Optimization

The Internet of Things (IoT) has revolutionized the way we live, work, and interact with our surroundings. Sensor systems play a crucial role in these technological advancements, and their integration with IoT has revolutionized the way data is acquired, processed, and utilized. This book offers a structured understanding of sensor technologies, principles, applications, and their integration into IoT systems, thereby bridging the gap between sensors and IoT applications.This book goes beyond theoretical explanations and stands out as a comprehensive and practical guide with a strong focus on real-world applications. It reveals some interesting aspects of such fascinating interactions between sensors and the IoT -- in particular, cutting-edge technologies and possibilities ranging from smart homes to industrial automation and beyond. It also offers a detailed exploration of sensors and the measurement principles characteristic of sensors designed to detect and measure specific environmental parameters -- especially those equipped with the capability to convert the collected data into electronic signals, which can then be processed and communicated to other connected devices through the internet. Data-based innovation in driving technological advancements is also addressed, and Intellectual Property (IP) is explored as a key element in bridging the gap between scientific research and marketable products.This book is an indispensable guide for students, researchers, and professionals alike. Its comprehensive approach to sensor technology makes it a valuable resource for scientists, engineers, and decision makers in industry.

Sensors And The Internet Of Things: Acquisition And Use Of Big Data

Increase efficiency, improve profitability and reduce spend and become more confident handling and analyzing customer data for further insight.

Strategies for Accuracy and Efficiency

Optimizing Sales and Marketing Data

Microsoft Power BI For Dummies

This book explores the latest advancements in machine learning techniques and their transformative applications in the healthcare domain. It delves into the use of machine learning for disease diagnosis and prognosis, showcasing its potential to enable accurate disease identification, effective risk stratification, and personalised treatment planning. The role of machine learning in enhancing clinical decision support systems (CDSS) is examined in detail, with a focus on its impact on informed decision-making, predictive modeling, and real-time patient monitoring.<ul> <li>Features real-world case studies and applications that demonstrate the practical use of machine learning in healthcare, including radiology, predictive analytics, personalised medicine, and resource optimisation.</li> <li>Covers essential stages of data preprocessing and feature engineering for healthcare datasets, addressing challenges such as data cleaning, normalisation, dimensionality reduction, and feature selection.</li> <li>Provides an in-depth overview of CDSS and the integration of machine learning algorithms to improve diagnostic accuracy and clinical workflow efficiency.</li> <li>Explores machine learning-driven real-time monitoring and alert systems, underscoring their utility in promptly identifying and responding to critical medical events.</li> <li>Discusses advances in medical image analysis, including segmentation, classification, and computer-aided diagnosis techniques.</li> </ul>This comprehensive volume serves as a valuable resource for researchers, clinicians, healthcare professionals, data scientists, and students seeking to understand and apply machine learning for improved healthcare outcomes.

Case Studies and Applications of Machine Learning in Healthcare

Tech Today

Add to your Excel toolkit by learning to implement advanced AI and automation techniques for data analysis As technology evolves all around us, professionals must keep learning new skills just to keep up with the heightened expectations of our leaders. That's especially true when it comes to artificial intelligence-related advancements in the field of data analysis. In Excel Power Tools: Unlocking the Power of AI, Python, and Power Automate, veteran analytics educator George Mount delivers a practical guide for everyday Excel users seeking to leverage the software's advanced features to import, clean, and analyze data. You'll learn to automate your data analysis and discover how to use power user features like pattern recognition, forecasting, and fuzzy matching. You'll: Develop a solid understanding of how to integrate AI into your work without radically changing the tools you use every dayLearn to use Python to automate routine data tasks and become more productive and efficientFind real-world examples of AI integration that illustrate the simple and accessible concepts discussed in the book Perfect for professionals in routine reporting roles, including accountants, data analysts, financial analysts, marketing coordinators, controllers, and operations analysts, Excel Power Tools is also a must-read for data science professionals and other technical experts who wish to unlock the full capabilities of Excel.

Unlocking the Power of AI, Python, and Power Automate

Excel Power Tools

Data Science

Graph Mining

Data-Directed Mathematical Modeling

Informations bibliographiques

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Informations bibliographiques

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