Mostrando títulos en Ciencia de Datos

Ever wondered how companies turn raw data into actionable insights or how data-driven decisions are made? "Fundamentals of Data Engineering" by Joseph Achakji is your gateway to understanding the intricate world of data engineering, a field that powers today's most innovative technologies and business strategies.

By combining relentless optimism with a brutally honest reflection on common data strategy mistakes and what it takes to fix them, Tiankai provides CxOs to operational staff, data experts to business users, and students to experienced leaders, a refreshing take on turning advocates into active change-makers to create a sustainable data strategy. People are emotional, irrational, and impulsive, but they also play a crucial part in any data strategy work. Yet why is the people part of data strategy so difficult? Tiankai decodes the human aspects of data strategy into an actionable framework, ...

Master the fundamentals of networking and confidently prepare for the Cisco Certified Network Associate (CCNA) exam with this comprehensive guide. This book equips you with the knowledge and skills required to excel in today's dynamic networking landscape.

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.

If you’re considering a shift to data analysis, you’re likely exploring various programming languages to kickstart your journey. Take a cue from industry giants like Netflix, Facebook, and Amazon, who rely on SQL for data analysis. Don’t let misconceptions hinder your data analysis journey. Equip yourself with this comprehensive guide and master SQL to unlock new opportunities.

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.

This book bridges the gap between strictly technical books about the blockchain and the research-based books primarily concerned with practical applications, discussions of its expected economic effect, and future visions. It will be your guide through the unknown and complicated world of cryptocurrency and blockchain technology.

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment.

Did you know that ChatGPT already boasts a community of over 100 million users? That's 100 million opportunities to make a splash in a still-young market. So, if you're tired of sitting on the sidelines, watching others take the prize, this guide is your game-changer, your treasure map, and your ticket to the big leagues — all powered by ChatGPT.

Learn what’s going wrong with data and how to fix it. My last book was about data crimes. We have to solve those crimes and prevent them from happening again. Data is too valuable to leave unattended. Pick and choose stories to read by subject, including data management, data lifestyle, data governance, data architecture, master data management, data modeling, data lakes, metadata, data quality, data privacy, data retention, and analytics. Use the stories to rethink what you’ve been doing and if you need or want to take a new approach. These stories come from a lifetime of working with ...

Businesses own more data than ever before, but it's of no value if you don't know how to use it. Data governance manages the people, processes, and strategy needed for deploying data projects to production. But doing it well is far from easy: Less than one fourth of business leaders say their organizations are data driven. In Designing Data Governance from the Ground Up, you'll build a cross-functional strategy to create roadmaps and stewardship for data-focused projects, embed data governance into your engineering practice, and put processes in place to monitor data after deployment.

From the ocean floor to outer space, China’s Digital Silk Road aims to wire the world and rewrite the global order. Taking listeners on a journey inside China’s surveillance state, rural America, and Africa’s megacities, Jonathan Hillman reveals what China’s expanding digital footprint looks like on the ground and explores the economic and strategic consequences of a future in which all routers lead to Beijing.

To succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery.

Understanding Ethereum now could equip you with the knowledge ahead of a major technological revolution in these early stages of development. After listening to this audiobook, you will understand how to easily set up an Ether wallet and then buy and trade Ether. This audiobook always contains information about mining Ether including cloud mining and more advanced Ethereum topics.

En un día promedio de principios del siglo xxi, los seres humanos que buscan en Internet acumulan ocho billones de gigabytes de datos. Esta asombrosa cantidad de información puede decirnos mucho sobre quiénes somos, los miedos, deseos y comportamientos que nos impulsan y las decisiones conscientes e inconscientes que tomamos. De lo profundo a lo mundano, podemos obtener un asombroso conocimiento sobre la psique humana que hace menos de veinte años parecía insondable.

El objetivo de Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Machine Learning es ayudarle a expandir sus habilidades de ser un científico de datos básico a convertirse en un científico de datos experto listo para resolver problemas centrados en datos del mundo real. Al final de este libro, aprenderá cómo combinar Aprendizaje automático, Minería de datos, análisis y programación, y extraer conocimiento real de los datos.

Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values, and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits, and identify new business opportunities.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.

Until very recently, if you were to ask most doctors, they would tell you there were only two kinds of medicine: the quack kind, and the evidence-based kind. The former is baseless, and the latter based on the best information human effort could buy. Well, Eric Topol isn't most doctors, and he suggests you entertain the notion of a third kind of medicine, one that will make the evidence-based state-of-the-art stuff look scarcely better than an alchemist trying to animate a homunculus in a jar.