Data Science Engineering

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. 

This comprehensive guide to Microsoft Azure Data Engineering is designed to elevate your skills in data analytics, pipeline development, and Azure cloud solutions. Dive deep into essential concepts like data integration, ETL, SQL, Data Lakes, storage management, Data Governance, Data Strategy and big data architecture. This eBook is a Number #1 Best Seller in the following categories: #1 Data Warehousing #1 Computer Engineering #1 SQL Programming In today's job market, skilled Azure Data Engineers are rare, and their compensation reflects that rarity. They enjoy substantial salaries and the...

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee.

Book Title: Handbook for Prompt Engineering: A Complete Guide and Examples for Prompt Engineering Science from Scratch to Application Unlock the full potential of AI-driven interactions with the definitive guide to prompt engineering. "Handbook for Prompt Engineering: A Complete Guide and Examples for Prompt Engineering Science from Scratch to Application" provides an authoritative and comprehensive exploration of the principles, techniques, and best practices essential for mastering prompt engineering in natural language processing (NLP) and artificial intelligence (AI). About the Book: ...

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. 

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. 

Are your data engineering and analytics teams overwhelmed by a fragmented ecosystem that makes generating actionable business insights nearly impossible? Today, enterprises are generating more data than ever, but most are paralyzed by disjointed tools, isolated data lakes, and complex multi-cloud architectures. When your data scientists and business analysts are forced to operate in silos using disconnected systems, the result is crippling inefficiency. This duplication of effort leads to the proliferation of Shadow IT, exorbitant costs from unshared computing resources, and massive ...

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

Machine Learning for Absolute Beginners Third Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required.

James Gleick, the author of the best sellers Chaos and Genius, now brings us a work just as astonishing and masterly: a revelatory chronicle and meditation that shows how information has become the modern era’s defining quality—the blood, the fuel, the vital principle of our world. The story...

If you found a rusty old lamp on the beach, and upon touching it a genie appeared and granted you three wishes, what would you wish for? If you were wishing for a successful application development effort, most likely you would wish for accurate and robust data models, comprehensive data flow diagrams, and an acute understanding of human behavior. The wish for well-designed conceptual and logical data models means the requirements are well-understood and that the design has been built with flexibility and extensibility leading to high application agility and low maintenance costs. The wish ...

Data Analytics for Absolute Beginners is your no-stress, no-nonsense guide to understanding and applying data analysis, even if you've never worked with data before. This hands-on, beginner-friendly guide is packed with practical examples, visual explanations, and two bonus Python exercises (with video tutorials) to walk you through real-world analysis scenarios.

This book provides a comprehensive exploration of feature engineering, hyperparameter tuning, model interpretability, and production-level machine learning practices. Designed for practitioners and advanced learners, it delves into the techniques, tools, and strategies required to build robust, scalable, and explainable machine learning systems. From automated pipelines to drift detection and continuous monitoring, each chapter bridges theory with practical implementation to equip readers with the skills needed to deploy and maintain high-performing models in real-world environments.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

In her second week at a logistics startup, a bootcamp graduate received a ticket that read, simply, “add machine learning to flag late shipments.” She spent two days searching for a model to download before a senior engineer asked one question: how do late shipments get labeled today? The answer was sitting in a single column of the orders table. The ticket needed a SQL query and an alert, not a neural network. She had reached for machine learning because the word was in the ticket — not because the problem required it. That story is where most ML introductions fail the people who ...

A data-driven, scientific account of our need for speed—exploring a wide range of topics including evolution, transportation, and technology In a world obsessed with efficiency, perhaps nothing is valued as highly as being fast. Some of our greatest achievements include building planes that...

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.