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This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability.You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS.By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!
Jonas Christensen, Nakul Bajaj, Manmohan Gosada, Kirk D. Borne
In the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets.This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of ‘small data’. Delving into the building blocks of data-centric ML/AI, you’ll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you’ll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you’ll get a roadmap for implementing data-centric ML/AI in diverse applications in Python.By the end of this book, you’ll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability.
Partha Pritam Deka, Joyce Weiner, Prof. Roberto V. Zicari
XGBoost offers a powerful solution for regression and time series analysis, enabling you to build accurate and efficient predictive models. In this book, the authors draw on their combined experience of 40+ years in the semiconductor industry to help you harness the full potential of XGBoost, from understanding its core concepts to implementing real-world applications.As you progress, you'll get to grips with the XGBoost algorithm, including its mathematical underpinnings and its advantages over other ensemble methods. You'll learn when to choose XGBoost over other predictive modeling techniques, and get hands-on guidance on implementing XGBoost using both the Python API and scikit-learn API. You'll also get to grips with essential techniques for time series data, including feature engineering, handling lag features, encoding techniques, and evaluating model performance. A unique aspect of this book is the chapter on model interpretability, where you'll use tools such as SHAP, LIME, ELI5, and Partial Dependence Plots (PDP) to understand your XGBoost models. Throughout the book, you’ll work through several hands-on exercises and real-world datasets.By the end of this book, you'll not only be building accurate models but will also be able to deploy and maintain them effectively, ensuring your solutions deliver real-world impact.
Mastering Customer Success. Discover tactics to decrease churn and expand revenue
Jeff Mar, Peter Armaly, Mark Stouse
The rapidly evolving customer success landscape has left many Customer Success Managers (CSMs) struggling to keep pace with the complexities of this dynamic role. This Customer Success book bridges the gap by providing a comprehensive framework for mastering the essential skills required to excel.You’ll find out why the Customer Success function is indispensable today and gain expert insights into account segmentation, financial tiering, ideal customer profiles, and the complexity of customer engagement process design. You’ll then delve into playbook development, where you’ll find practical guidance for CSMs and Customer Success Operations Managers who want to improve their ability to drive desired business outcomes. Through insightful case studies, the authors illustrate their own experience of successful Customer Success implementation, showing you what it takes to exceed customer expectations with well-designed, proactive services. The journey doesn’t end there—it extends to highlighting the resilience required to build and operate successful Customer Success organizations.By the end of this guide, you’ll be equipped with the tactics and mindset necessary to stand out as a world-class Customer Success leader in your organization, driving growth at every turn.
Mastering Tableau. Smart Business Intelligence techniques to get maximum insights from your data
Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0.You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool’s inner workings and creatively exploring possibilities. You’ll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently.By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau.
Rafał Świdziński, Alexander Kushnir
Modern CMake for C++ isn't just another reference book, or a repackaging of the documentation, but a blueprint to bridging the gap between learning C++ and being able to use it in a professional setting. It's an end-to-end guide to the automation of complex tasks, including building, testing, and packaging software.This second edition is significantly rewritten, restructured and refreshed with latest additions to CMake, such as support of C++20 Modules.In this book, you'll not only learn how to use the CMake language in CMake projects but also discover how to make those projects maintainable, elegant, and clean. As you progress, you'll dive into the structure of source directories, building targets, and packages, all while learning how to compile and link executables and libraries. You'll also gain a deeper understanding of how those processes work and how to optimize builds in CMake for the best results. You'll discover how to use external dependencies in your project – third-party libraries, testing frameworks, program analysis tools, and documentation generators. Finally, you'll gain profi ciency in exporting, installing, and packaging for internal and external purposes.By the end of this book, you'll be able to use CMake confi dently at a professional level.
GraalVM is a universal virtual machine that allows programmers to compile and run applications written in both JVM and non-JVM languages. It improves the performance and efficiency of applications, making it an ideal companion for cloud-native or microservices-based applications.This book is a hands-on guide, with step-by-step instructions on how to work with GraalVM. Starting with a quick introduction to the GraalVM architecture and how things work under the hood, you'll discover the performance benefits of running your Java applications on GraalVM. You'll then learn how to create native images and understand how AOT (ahead-of-time) can improve application performance significantly. The book covers examples of building polyglot applications that will help you explore the interoperability between languages running on the same VM. You'll also see how you can use the Truffle framework to implement any language of your choice to run optimally on GraalVM.By the end of this book, you'll not only have learned how GraalVM is beneficial in cloud-native and microservices development but also how to leverage its capabilities to create high-performing polyglot applications.