Май 22, 2015 - 0 Comments - Без рубрики -

Big Data дайджест #1. Визуализация данных

Intro

Зачем нужны инструменты визуализации данных?
Визуальная информация лучше воспринимается и позволяет быстро и эффективно донести до зрителя мысли и идеи. Физиологически восприятие такой информации является основной для человека.

— datajournalism.stanford.edu
Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium. But how do we communicate with data, how can traditional narratives be fused with sophisticated, interactive information displays?

Articles

— The Architecture of a Data Visualization. Multilayered Storytelling through “Info-spatial” Compositions.
— A Tour Through the Visualization Zoo.

News & Trends

— flowingdata.com
“The greatest value of a picture is when it forces us to notice what we never expected to see.” FlowingData explores how statisticians, designers, data scientists and others use analysis, visualization and exploration to understand data and ourselves.

— visual.ly
Visually’s mission is helping you to create visual content that rises above the noise. Our platform seamlessly connects designers, journalists, animators and developers with clients, featuring cloud-based collaboration tools that allow us to deliver high-quality content at unprecedented scale and speed.

— informationisbeautiful.net
Information Is Beautiful. We love visualizing information. Not just data and statistics. But ideas, stories, knowledge, issues — all the different kinds of information that swamp us every day. We’re interested in how designed information can help us understand the world, cut through BS and reveal hidden connections, patterns and stories underneath. Or, failing that, it can just look cool!

— datasciencecentral.com
Data Science Central is the industry’s online resource for big data practitioners. From Analytics to Data Integration to Visualization, Data Science Central provides a community experience that includes a robust editorial platform, social interaction, forum-based technical support, the latest in technology, tools and trends and industry job opportunities.

Education

— datajournalismcourse.net
A free online data journalism course with 5 leading experts. This Data Journalism Course, or MOOC, is part of the European Journalism Centre’s Data Driven Journalism initiative, which aims to enable more journalists, editors, news developers and designers to make better use of data and incorporate it further into their work.

— Data Visualization (MS). School of art, media, and technology. This interdisciplinary graduate program brings together design, statistics, and computer science, developing your critical abilities and facility for innovation in work settings in which data increasingly shapes opinion, policy, and decision making in all sectors.

— Data visualisation at Coursera
Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation.

— Udacity
Learn the fundamentals of data visualization and practice communicating with data. This course covers how to apply design principles, human perception, color theory, and effective storytelling to data visualization. If you present data to others, aspire to be an analyst or data scientist, or if you’d like to become more technical with visualization tools, then you can grow your skills with this course.

— In this course we will study techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science. The course is targeted both towards students interested in using visualization in their own work, as well as students interested in building better visualization tools and systems.

Books

— The Visual Display of Quantitative Information. Edward R. Tufte.
The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis.

— The Wall Street Journal Guide to Information Graphics: The Dos and Don’ts of Presenting Data, Facts, and Figures. Dona M. Wong
The definitive guide to the graphic presentation of information. In today’s data-driven world, professionals need to know how to express themselves in the language of graphics effectively and eloquently. The book is organized in a series of mini-workshops backed up with illustrated examples, so not only will you learn what works and what doesn’t but also you can see the dos and don’ts for yourself.

— Visual Storytelling with D3: An Introduction to Data Visualization in JavaScript (Addison-Wesley Data & Analytics Series). Ritchie S. King
Data-driven graphics are everywhere these days, from websites and mobile apps to interactive journalism and high-end presentations. Visual Storytelling with D3 is a hands-on, full-color tutorial that teaches you to design charts and data visualizations to tell your story quickly and intuitively, and that shows you how to wield the powerful D3 JavaScript library.

— Information Dashboard Design: Displaying Data for At-a-Glance Monitoring. Stephen Few
According to the author, dashboards have become a popular means to present critical information at a glance, yet few do so effectively. The book not only teaches how to design dashboards but also gives a deep understanding of the concepts—rooted in brain science—that explain the why behind the how.

— Data Science for Business: What you need to know about data mining and data-analytic thinking. Foster Provost, Tom Fawcett.
Written by renowned 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.

— Mathematica Data Visualization. Nazmus Saquib
Create and prototype interactive data visualizations using Mathematica. Understand visualization functions used by scientists, engineers, and financial analysts. Build a visualization system from scratch using low-level graphics primitives and interactive functionalities. Learn how to visualize a wide range of datasets with the help of detailed explanations of code and theory.

Tools for Data Visualization

Collections

— visualisingadvocacy.org
Whether you are trying to clean your data, spot patterns, or create a data visualisation, there are many free tools available online. Finding the right tool for your need and skill level, however, can be difficult. We have been testing out tools and profiling them below to help you decide which ones are best for the job you are trying to do.

— Datavisualization.ch Selected Tools is a collection of tools that we, the people behind Datavisualization.ch, work with on a daily basis and recommend warmly. This is not a list of everything out there, but instead a thoughtfully curated selection of our favorite tools that will make your life easier creating meaningful and beautiful data visualizations.

Microsoft

— powerbi.com
Microsoft Power BI is a collection of online services and features that enables you to find and visualize data, share discoveries, and collaborate in intuitive new ways. There are two experiences now available for Power BI: the current experience, generally referred to as Power BI for Office 365, and a new experience for Power BI, currently offered as a Public Preview.

— Microsoft Research Data Visualization Apps for Office. A histogram shows the distribution of data. A 2D Histogram, or Density Plot, visualizes the joint distribution of two different axes. A treemap is a hierarchical view of data. A Streamgraph shows the way that a set of numbers has changed over time by their relative area.


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