Lynda - CSS Formatting Visual Data
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Wonderful writeup, as always. One question on semantics, though. On sites like The Verge, there are usually grids of articles laid out in a very table-like style. While you say that tables should only be used for tabular data, I argue that layout like this is in fact tabular data. The convention rarely appears outside of blog homepages, but it does in fact perform the original function of a table: to lay out value in a visually-organized manner.
Complex content images, such as illustrations, diagrams, and charts, require more lengthy descriptions than can be included in an alt attribute. In many cases, the best approach is to include a caption with the image, which benefits all users in comprehending the information contained in the image. For example, for a chart that shows lifespan increase over time, include the data in an accessible table with the image. That way screen reader users have access to the same information, and people who comprehend numbers better than visualizations also benefit. HTML5 provides the and elements to make a programmatic connection between image and caption.
Kids InfoBits is a database developed especially for beginning researchers in Kindergarten through Grade 5. Featuring a developmentally appropriate, visually graphic interface, the most popular search method is moving from a broad subject to a narrower topic using the subject-based topic tree. The curriculum-related, age appropriate, full-text content is from the best elementary reference sources and magazines. This database covers geography, current events, the arts, science, health, people, government, history, sports and more.
In this age and times of Technology and Big Data, Data visualization is increasingly becoming an absolute must-learn skill. As organizations become more and more data driven, not only do we need to interpret large amounts of data, but also be able to analyze, explain, digest and compare complex data in a manner that it is accessible to anyone who needs understanding of that data.
Also because of the way our human brain processes information, visually-displayed data in the form of charts or graphs etc is easier to understand than sets of spreadsheets and reports. A well thought out visualization peels back the layers surrounding a raw dataset. All businesses these days are therefore leveraging Data Visualization to analyse information faster, recognise patterns and trends, and find valuable insights. Organizations of all sizes are looking for Data Visualization experts. So the ability to work with data is not just a bonus skill, but an essential one, in fact it is the highest ROI skill in current times.
Data Visualization is not just limited to the field of data scientists and data analysts, in all careers whether finance, marketing, tech, design, etc. there is a need for data communicators who can visualize data and convey results effectively to both technical and non-technical people.
This Tableau training for Data Visualization has been developed by University of California in collaboration with Tableau and offered via Coursera platform. It is one of the best combinations of theory and practical training in Tableau that starts with the fundamental concepts of data visualization, and various tools that Tableau has to offer and builds from there to finally creating multi-frame data stories in Tableau.
This is a beginner level Data Visualization using Tableau certification program, and is an excellent fit for anyone who is comfortable working with data and datasets and wants to get started with learning data visualization and tableau. No prior technical or analytical background is required to enrol in this specialization.
This Data Visualization online course has been created by IBM and is available on Coursera. It is rated amongst the top data visualization with Python courses with more than 85K students already enrolled in the course. It teaches learners how to leverage Python to visualize data to enable them to extract information, better understand the data, and make more effective decisions. It covers several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium that are used to present the data visually.
Upon completing this data visualization training course, learners are able to take any seemingly meaningless data set and present it in a form that others can comprehend well and make sense of. It is intended for intermediate users with some experience in Python and handling data.
This Course on Data Visualization with Tableau is offered by Duke University as part of its Excel to MySQL: Analytic Techniques for Business Specialization. The goal of this course is to prepare learners to become an expert at communicating business-relevant practical implications of their data analyses. It teaches them to streamline their analysis by asking the right questions and use Tableau to convey critical findings. Students learn Storyboarding skills and how to visualize the results of data analysis or machine learning models in Tableau, so that it can be better understood by both technical and non-technical stakeholders.
Together these two Tableau courses have more than 270000 students enrolled with an average rating of 4.6 and favourable reviews. The series has more than 18 hours of video content and focuses mostly on the coverage of Tableau tool, rather than the theory of data visualization. Let us look at each of these courses in some detail.
This is the first course in the series and offers a practical step-by-step guide to learning tableau with real-life examples, data analytics exercises and assignments. It covers in detail all the features in Tableau that are used to explore, experiment with, fix, prepare, and analyse raw data and convert it into compelling data visualizations. Following topics are covered in this Tableau tutorial:
This is the second and more advanced course in the series of Tableau udemy courses by Kirill Eremenko. It dives into depth on some of the most powerful features of Tableau. It promotes learning data visualization and data mining by doing, for which it uses unique datasets and engaging exercises to solve real life analytics problems. Following topics are covered in this Tableau class:
This Data Visualization program offered by Udacity is a world-class, cutting edge training program to build data visualization and communication skills. Udacity has collaborated with Tableau, the most popular data visualization tool, along with an excellent group of industry professionals with extensive experience to create curriculum that focuses on most in-demand skills. The program teaches learners to create clear and impactful data visualizations and use their analysis to make data-driven recommendations.
A lot of focus of this Data Visualization certification program is on building storytelling skills. Since, stories offer a powerful way to draw in the audience, make sense of the data and help businesses make better decisions, this program teaches learners how to weave data into stories and visuals using various tools and techniques. Two data visualization platforms Tableau and Flourish are covered in the program.
This course has been created by PricewaterhouseCoopers (PwC) and is part of their Data Analysis and Presentation Skills: the PwC Approach Specialization. This goal of this course is to help learners expand their analytical skills by answering questions and telling a story with their data. It uses Excel to develop data visualization skills as Excel is the most widely used software tool and is easily available to most learners.
This course has been created by Jose Portilla and is available on Udemy. The goal of this course is to provide learners with a complete understanding of Python and how it can be used effectively to analyse and visualize data. This course covers NumPy, pandas, how to import and export data in Python, how to visualize that data with Python libraries and data portfolio projects. It also touches upon Machine learning with Scikit-Learn. In addition to all of this it has appendix materials including materials on Statistics, using SQL with Python and how to perform webscraping with Python.
D3.js is a JavaScript library for data visualization; very powerful for creating visually appealing charts, maps, flows, live and interactive graphs and other data-driven visualizations. This Udemy Data Visualization course, developed by Adam Janes, provides a comprehensive introduction to D3.js library and how to use it to design and create impressive data visualizations. It takes learners from being complete novices to D3 to being able to develop any visualization they could imagine. Not only does it teach learners to create common charts and graphs, but also provides them with tools to pick up any visualization by themselves.
This Data Visualization class is intended for learners who already have some experience at programming on the web and want to learn about data visualization design and build complex interactive websites with D3js.
Learners can take edX Data Visualization courses to gain foundational skills in data visualization, learn to use various tools and software to perform data analyses and combine data with visuals in order to create impactful presentations that help to make sound business decisions.
This course by Harvard University is part of their Professional Certificate program in Data Science. It teaches the basics of data visualization and exploratory data analysis and how to apply the data visualization principles using ggplot2 (data visualization package for the statistical programming language R). This course covers the following topics: 2b1af7f3a8