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Название: Everyday Data Visualization: Design Effective Charts and Dashboards (Final Release)
Автор: Desiree Abbott
Издательство: Manning Publications
Год: 2024
Страниц: 264
Язык: английский
Формат: epub (true)
Размер: 32.4 MB

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. This book gives you the tools you need to bring your data to life with clarity, precision, and flair. You’ll learn how human brains perceive and process information, wield modern accessibility standards, get the basics of color theory and typography, and more. One of the most popular and powerful data visualization libraries for jаvascript is the free and open-source d3.js, also known as D3 or d3, which stands for “Data-Driven Documents.” If jаvascript and its asynchrony aren’t your jam, perhaps you’d prefer Python or R. While Python is an entire programming language, and R is a software environment specifically made for statistical analysis, both are free and open source, have a cult-like following among coders, and are great for data viz practitioners. Both R and Python have very friendly and approachable syntax, hence their considerable popularity. If you’re a statistician or data scientist, you probably already know R, and if you’re not, I’d wager you’d prefer Python. As for libraries to use in each, R users adore their ggplot/ggplot2 and Shiny, while Python users have many other options, including Seaborn, Plotly, and Matplotlib.

Название: Excel Cookbook (Early Release)
Автор: Dawn Griffiths
Издательство: O’Reilly Media, Inc.
Год: 2024-05-14
Страниц: 437
Язык: английский
Формат: epub
Размер: 16.5 MB

Filled with tips, tricks, and techniques, this easy-to-use book is the perfect resource for intermediate to advanced users of Excel. You'll find complete recipes for more than a dozen topics covering formulas, PivotTables, charts, Power Query, and more. Each recipe poses a particular problem and outlines a solution that you can put to use right away—without having to comb through tutorial pages. Whether you're a data analyst, project manager, or financial analyst, author Dawn Griffiths directs you straight to the answers you need. Ideal as a quick reference, Excel Cookbook is also perfect for learning how to work in a more efficient way, leading to greater productivity on the job. With this book, you'll jump in and get answers to your questions—fast. Whether you’re a data analyst, project manager, financial analyst, or regular Excel user, author Dawn Griffiths directs you straight to the answers you need. Ideal as a quick reference, Excel Cookbook is also perfect for learning how to work in a more efficient way, leading to greater productivity on the job. With this book, you'll jump in and get answers to your questions—fast.

Название: Ultimate Snowflake Architecture for Cloud Data Warehousing: Architect, Manage, Secure, and Optimize Your Data Infrastructure Using Snowflake for Actionable Insights and Informed Decisions
Автор: Ganesh Bharathan
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 325
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Unlocking the Power of Snowflake: Unveiling the Architectural Wonders of Modern Data Management. Unlock the revolutionary world of Snowflake with this comprehensive book which offers invaluable insights into every aspect of Snowflake architecture and management. The Snowflake database revolutionized cloud-based databases with its unique hybrid of shared disk and shared-nothing architectures, paving the way for a rather groundbreaking approach that has become a solution for many organizations that were tied to service providers who provided a coupled compute and storage solution. Beginning with an introduction to Snowflake's architecture and key concepts, you will learn about cloud data warehousing principles like Star and Snowflake schemas to master efficient data organization. Advancing to topics such as distributed systems and data loading techniques, you will discover how Snowflake manages data storage and processing for scalability and optimized performance. Covering security features like encryption and access control, the book will equip you with the tools to ensure data confidentiality and compliance. The book also covers expert insights into performance optimization and schema design, equipping you with techniques to unleash Snowflake's full potential.

Название: Инструментарий хранения и анализа данных. Полное руководство по размерному моделированию
Автор: Марджи Росс, Ральф Кимбалл
Издательство: Эксмо
Год: 2024
Формат: pdf
Размер: 11 Мб
Качество: Хорошее
Язык: Русский

Сегодня тысячи компаний собирают и сохраняют большие данные о поведении своих клиентов, ассортименте, производственном процессе и других немаловажных для бизнеса вещах. Однако, чтобы принимать обоснованные решения на основе этих данных, недостаточно их просто собрать – нужно правильно их обработать и провести грамотный анализ. Благодаря этой книге вы освоите все необходимые инструменты для хранения и анализа большого количества данных, научитесь правильно управлять ими и извлекать полезную информацию для развития бизнеса.

Название: ClickHouse для аналитика
Автор: Николай Петров
Издательство: Stepik
Год: 2023
Формат: HTML
Страниц: много
Размер: 107 Mb
Язык: Русский

ClickHouse это одна из самых быстро развивающихся СУБД и платформ для работы с данными. Инвестиции в изучение этого инструмента сейчас, дадут вам большие возможности потом. Для примера, эту СУБД внедрили Spotify и даже Uber! На курсе мы разберемся как оно устроено под капотом, а также напишем много SQL.

Название: Augmented Analytics: Enabling Analytics Transformation for Data-Informed Decisions (3rd Early Release)
Автор: Willi Weber, Tobias Zwingmann
Издательство: O’Reilly Media, Inc.
Год: 2024-04-30
Страниц: 307
Язык: английский
Формат: epub
Размер: 10.1 MB

Augmented Analytics isn't just another book on data and analytics; it's a holistic resource for reimagining the way your entire organization interacts with information to become insight-driven. Moving beyond traditional, limited ways of making sense of data, Augmented Analytics provides a dynamic, actionable strategy for improving your organization's analytical capabilities. With this book, you can infuse your workflows with intelligent automation and modern artificial intelligence, empowering more team members to make better decisions. Be aware: These pages cover more than just adding another forecast to your dashboard. They go deeper, presenting a complete approach to achieving analytical excellence in your organization. This book covers many aspects, both methodological and technical, of the broad topic of analytics transformation. The methodological topics are particularly foundational for understanding analytics maturity while the technical topics help you increase that maturity. The book is particularly valuable for experienced analysts and for people in strategic and managerial positions who are responsible for some facet of an analytical or digital transformation. You will see in these pages many transformative concepts and ideas that have a strong strategic character. You will also see technical implementations in dedicated analytics programming languages, such as Python and R. But even if you are not an analytics professional with programming skills, this book is for you: we explain all concepts, including the technical implementations, in a way that business professionals can understand while providing a complement for people who would like to dive deeper technically.

Название: Переходим на Mac
Автор: Макфедрис П.
Издательство: М: Манн, Иванов и Фербер
Год: 2013
Cтраниц: 384, цвет.ил.
Формат: pdf
Размер: 40 мб
Язык: русский

Эта книга - персональный консультационный центр, который поможет ответить на все вопросы, возникающие при переходе из Windows в среду Apple. Из неё вы узнаете как уютно обустроить ваше новое компьютерное пространство; изучите все особенности интерфейса; научитесь устанавливать программы из App Store; узнаете, как синхронизировать данные с iPhone, iPod или iPad и обеспечить общий доступ к данным из Mac OS Х и Windows; сможете грамотно организовать выполнение повседневных задач и работу с важными данными; научитесь самостоятельно исправлять большую часть неполадок.

Название: Statistical Tableau: How to Use Statistical Models and Decision Science in Tableau
Автор: Ethan Lang
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 314
Язык: английский
Формат: epub (true)
Размер: 24.4 MB

In today's data-driven world, understanding statistical models is crucial for effective analysis and decision making. Whether you're a beginner or an experienced user, this book equips you with the foundational knowledge to grasp and implement statistical models within Tableau. Gain the confidence to speak fluently about the models you employ, driving adoption of your insights and analysis across your organization. As AI continues to revolutionize industries, possessing the skills to leverage statistical models is no longer optional—it's a necessity. Stay ahead of the curve and harness the full potential of your data by mastering the ability to interpret and utilize the insights generated by these models. Whether you're a data enthusiast, analyst, or business professional, this book empowers you to navigate the ever-evolving landscape of data analytics with confidence and proficiency. Start your journey toward data mastery today. Statistical analysis and data visualization are often considered two separate things. However, both disciplines rely on one another. To understand your data and make accurate predictions or assumptions through statistical analysis, you must visualize your data. On the other hand, to deliver actionable insights and enable your audience to get the most from data visualizations, we must back up our assumptions with some statistical analysis. This book is to help you bring statistics into your visualizations in Tableau. You will learn how to read and interpret statistical models, implement them in Tableau, and ultimately draw out actionable insights to present to your stakeholders. Most decisions using data come with risks; it is your responsibility to arm the decision maker with as much information as possible and to mitigate those risks. R is a programming language and open source software environment primarily used for statistical computing and graphics. Python is a popular language in various fields, including web development (using frameworks like Django and Flask), Data Science and Machine Learning, and automation.

Название: Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance, and Scalability on the Data Lake
Автор: Tomer Shiran, Jason Hughes, Alex Merced
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 479
Язык: английский
Формат: pdf, epub (true)
Размер: 14.0 MB

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool—a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, Machine Learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. In these pages, you’ll learn what Apache Iceberg is, why it exists, how it works, and how to harness its power. Designed for data engineers, architects, scientists, and analysts working with large datasets across various use cases from BI dashboards to AI/ML, this book explores the core concepts, inner workings, and practical applications of Apache Iceberg. By the time you reach the end, you will have grasped the essentials and possess the practical knowledge to implement Apache Iceberg effectively in your data projects. Whether you are a newcomer or an experienced practitioner, Apache Iceberg: The Definitive Guide will be your trusted companion on this enlightening journey into Apache Iceberg.

Название: Big Data Analytics: Theory, Techniques, Platforms, and Applications
Автор: Ümit Demirbaga, Gagangeet Singh Aujla, Anish Jindal
Издательство: Springer
Год: 2024
Страниц: 299
Язык: английский
Формат: pdf (true), epub
Размер: 39.8 MB

This book introduces readers to Big Data analytics. It covers the background to and the concepts of Big Data, Big Data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the Big Data analytics working environments in the first two chapters. The third chapter provides comprehensive information on Big Data processing systems - from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of Big Data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of Big Data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending Machine Learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for Big Data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their Big Data analytics skills using various Big Data analytics frameworks.