Data Science Design

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.

In her new audiobook, Invisible Women, award-winning campaigner and writer Caroline Criado Perez shows us how, in a world largely built for and by men, we are systematically ignoring half the population. She exposes the gender data gap - a gap in our knowledge that is at the root of perpetual, systemic discrimination against women and that has created a pervasive but invisible bias with a profound effect on women’s lives.

Data is fundamental to the modern world. From economic development, to healthcare, to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, treating men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias in time, money, and often with their lives. Celebrated feminist advocate Caroline Criado Perez investigates the shocking root cause of gender inequality and research in Invisible Women.

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.

This is a print companion to the Massive Open Online Course (MOOC), Data Structures: An Active Learning Approach (https://www.edx.org/course/data-structures-an-active-learning-approach), which utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. While this print companion contains all STOP and Think questions, which will help you reflect on the material, and all Exercise Breaks, which will test your knowledge and understanding of the concepts ...

Designed for students and professionals in exercise science, kinesiology, and sports medicine, Muscle University: Research Foundations in Exercise Science provides an authoritative, practical, and comprehensive guide to conducting rigorous scientific research. This textbook combines foundational research theory with hands-on laboratory practice, equipping readers with the critical skills required for designing, implementing, and analyzing exercise science research. Key Features Include: Research Foundations: Clear, accessible explanations of experimental and observational research designs, ...

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.

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...

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.

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.

Celebrated data-driven growth leader Lillian Pierson delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.

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.

Data projects are an intrinsic part of an organization's technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more.

One key responsibility of product designers and UX practitioners is to conduct formal and informal research to clarify design decisions and business needs. But there’s often mystery around product research, with the feeling that you need to be a research Zen master to gather anything useful. But anyone can conduct product research. With this quick reference guide, you’ll learn a common language and set of tools to help you carry out research in an informed and productive manner.

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 ...

Centralized data warehouses, the long-time de facto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services.

With the death of Steve Jobs in 2011, Jony Ive has become the most important person at Apple. Some would argue he always was. Steve Jobs discovered Ive in 1997, when he found the scruffy British designer toiling away in a studio surrounded by hundreds of sketches and prototypes. Jobs instantly realised he had found a talent who could reverse Apple's decline, and become his 'spiritual partner'. Their collaboration produced iconic products including the iMac, iPod, iPad and iPhone - designs that overturned entire industries and created the world's most powerful brand.

Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

Radically improve the quality of your data visualizations by employing core principles of color, typography, chart types, data storytelling, and more. Everyday Data Visualization is a field guide for design techniques that will improve the charts, reports, and data dashboards you build every day. Everything you learn is tool-agnostic, with universal principles you can apply to any data stack.