Showing results by publisher "-emdashery books-" in Data Science

Scott Hartley first heard the terms fuzzy and techie while studying political science at Stanford University. If you majored in the humanities or social sciences, you were a fuzzy. If you majored in the computer sciences, you were a techie. This informal division has quietly found its way into a default assumption that has misled the business world for decades: that it's the techies who drive innovation.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

The Real Business of Blockchain is one of the first audiobooks on this transformative technology written for business leaders. Authors David Furlonger and Christophe Uzureau - both of Gartner, the world-renowned research and advisory company - will help you: assess how blockchain will impact your business by cutting through the hype and finding the real story; explore the value proposition that blockchain technologies offer; make smart near- and mid-term investments in your blockchain strategy; and position you and your organization in a new competitive landscape in the future.

The data your company generates is enormously valuable. But without the right strategy, you’ll never unlock that value - and you might even put your company at risk. Data Leverage is the first comprehensive book on the exploding opportunity of corporate data partnerships. The authors, Christian and Jay Ward, are experts - a business strategist and a lawyer who, together, have executed hundreds of deals.

Every new version of Java is important, but Java 8 was a game changer. Java 8 in Action is a clearly written guide to the new features of Java 8. It begins with a practical introduction to lambdas, using real-world Java code. Next, it covers the new Streams API and shows how you can use it to make collection-based code radically easier to understand and maintain.

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

A revolution is under way across the globe, yet very few people understand it. Basic Blockchain explains everything you need to know to understand the technology that will soon disrupt and revolutionise everything from financial and health services to the property market and how we vote.

Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices.

Do you need to learn how to use SQL in order to properly manage a database? Do you want to learn SQL programming without complicated explanations? SQL for Beginners: A Step by Step Guide to Learn SQL Programming and Database Management Systems is an easy to digest and fast-paced guide to learning Structured Query Language (SQL), which is the industry standard programming language for defining and analyzing data in databases. The audiobook will focus on how to use SQL in order to process your data and find out what it means.

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

This is a two-book bundle related to C++ programming and data analytics! Two manuscripts for the price of one!

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

Lars Nielsen and Noreen Burlingame provide a brief, understandable, user-friendly guide to all aspects of Data Science. The authors address the various skills required, the key steps in the Data Science process, software technology related to the effective practice of Data Science, and the best rising academic programs for training in the field.

As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization.

Data and analytics are essential for any business, giving insight into what's working, what can be improved, and what else needs to be done. SAS software helps you make sure you're doing data right, with a host of data management, reporting, and analysis tools. SAS For Dummies teaches you the essentials, helping you navigate this statistical software and turn information into value. In this book, learn how to gather data, create reports, and analyze results. You'll also discover how SAS machine learning and AI can help deliver decisions based on data.

Data Science Essentials For Dummies is a quick reference on the core concepts of the exploding and in-demand data science field, which involves data collection and working on dataset cleaning, processing, and visualization. This direct and accessible resource helps you brush up on key topics and is right to the point—eliminating review material, wordy explanations, and fluff—so you get what you need, fast.

Imagine a world where your data isn’t controlled by faceless corporations. A world where the internet isn’t a walled garden, but a boundless frontier of freedom, security, and opportunity. Welcome to Decentralizing the Future: The Story of Flux and the Rise of Web3. In this riveting journey, we unravel the story of the internet’s next great leap from the centralized grip of Web2, where a handful of tech giants hold the keys, to the decentralized promise of Web3. At the heart of this revolution is Flux, a trailblazer building the backbone of a new digital world.

Data Leadership for Everyone is a game-changing book for anyone who believes in the power of data and is ready to create revolutionary change in their organization. Whether you're a C-suite executive, a manager, or an individual contributor, this book will propel your career by unlocking the mystery of how raw data transforms into real outcomes.

In "Information vs Data" Ira Warren Whiteside redefines how we perceive and utilize information and data in today's technological environment. This book integrates advanced concepts of artificial intelligence (AI) and business intelligence (BI) to demonstrate their impact on modern industries.

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.