My data visualization and presentation workshop engages you and your staff or conference participants for a full day. You will learn the principles behind focused messaging and high-quality data presentation as taught by the leaders in the field. You will then move on to hands-on application of these principles as we build, and rebuild, some of the classic data graphics and tackle some of the newer forms, like bullet charts and heat maps. We will finish by learning to incorporate the new charts in succinct and engaging digital reports.
My approach to this emphasizes the principles behind good visual data presentation, so that you can make good decisions for any kind of data, report or audience, and so that you can continue to learn more while avoiding the stuff out there that is, frankly, junk. This isn’t just about how to make a collection of charts.
My approach is shaped by my experience in a range of data-driven communications environments, including political messaging and government relations working with mayors and councillors of Canada’s largest cities. That taught me how to focus on the message and tell a story, fast. To that I’ve added principles-driven data design and presentation.
I’ve done various versions of this for conferences of the Canadian Evaluation Society (CES), learning events and special workshop engagements with the CES National Capital, Prince Edward Island and (in April0 Nova Scotia Chapters and for clients including the Atlantic Canada Opportunities Agency and the Agency for Co-operative Housing, Canada. It gets better every time as I pick up new ideas and challenges from participants.
A few years ago, as I was getting seriously into this data visualization stuff, I decided to go straight to the top and travelled to Boston and View, California, to take training with with Stephen Few and Duarte Design, prominent among the original leaders in effective data visualization and presentation design. What I learned sharpened my approach to data presentation immeasurably. My course material is also based on diverse perspectives and contributions, from academics and practitioners of cognitive science and data presentation all the way to the world of sleight of hand and magic.
I have been delivering this course as a pre-conference workshop at the Canadian Evaluation Society Annual Conference and at CES learning events for the past several years. I’ve also given the full course to staff of the audit and evaluation directorates at the Atlantic Canada Opportunities Agency, and in part to the management and staff of The Agency for Cooperative Housing. The response to these courses is always very positive. Nevertheless, I learn how to improve it every time I deliver it. As a result, depending on your strong points and needs, I can put more weight on briefing and reporting strategies or on data and chart design.
The course is designed to fit into one fairly intense day, with the content falling into the areas of:
The first part of the day is spent learning about focussing messages and discarding the chaff, then on to the principles behind effective data presentation and how to apply them. Examples of common, but poor, data graphic designs and how to transform them, usually very easily, into effective designs help to illustrate the principles.
In this section, you will work with supplied datasets and follow along with me, but I provide worked examples and instructions for all of the data graphics that we build, so that you can refresh your memory, practice, and use the examples as templates for your own work.
We’ll then look at some applications of your new charts, including examples of visual analysis, dashboards/displays and interactive displays.
An important part of this will be a look at visualizing qualitative data, taking advantage of the pictorial superiority effect and principles based on characteristics of visual perception and memory. Many chart forms that are often used for quantitative data visualization are easily and effectively adapted to representing qualitative data, where there are relationships between qualitative data and concepts.
We will look at how to handle relational data, where one thing connects somehow to another, to handle both quantitative and qualitative information.
Other visual concepts are available as well, as promoted by Nancy Duarte and company, where an abstract concept, like “convergence” or “connection”, needs reinforcement.
We’ll cover approaches to infographics that emphasize informative content and storyline and avoid the common pitfalls of “data decoration”.
We will then return to another hands-on session on building more advanced devices like table lenses, small multiples and heat maps and combining them into well-designed visual data analyses, dashboards and displays.
Participants will receive a written step-by-step summary of the course content and an Excel or Tableau (see knowledge and equipment requirements) workbook containing worked examples and sample data, so that learning is easily reinforced and continued.
When we are finished, you’ll know how to use data visuals to focus your message; you can apply your new knowledge on which chart will work best for what data and circumstance, and how to use purposeful chart design and colour to maximize the effectiveness of your data and make your work compelling and, dare I say it, beautiful. You’ll also know how to situate your beautiful new charts in documents and report forms that draw the reader in and keep them. You will have new options for digital reporting that will make people glad to see what you’ve got for them, because you will inform them and you won’t waste their time with thick reports and extraneous verbiage. And because your work will just be so damned cool.
Understanding what social media is saying about your event, announcement, product or issues is a big advantage. So is identifying those people and organizations that are well-placed to connect others and spread your messages in the web that Twitter traffic produces.
This new one-day course is based on my social network analysis expertise and experience on various projects and more specifically on recent experience in mapping Twitter traffic for conference organizers. We will map Twitter messages in this course. You can then go on yourself to apply these techniques to other data like Facebook and email. The image below is a mapping of Twitter traffic generated by the Canadian Evaluation Society Annual Conference in June 2016. See also the address by outgoing American Evaluation Association President John Gargani at the closing plenary of the AEA Annual Conference 2016, where at the 1:30 mark through 3:25 he discusses our Twitter mapping of that conference and what it revealed: https://www.dropbox.com/s/8yaksw0ibb3vip7/Closing%20Plenary.mp4?dl=0
You need to know a bit about how social network analysis works before you can jump in and start mapping your social media. I’ll get you up to speed on the basics and the key characteristics of networks to look for and measure. Again, you will probably “get the bug” and want to learn more on your own, later. This part of the day will focus on:
basics of social network analysis
links and nodes
We’ll then take the first step into the driver’s seat. We’ll start working with NodeXL, which is probably the best and most straight forward social network analysis software for social media analysis. We’ll first cover data – using a simple dataset as an example:
node and attribute data
loading data and understanding the data editor
The next step will be analysis – we’ll generate and interpret:
groups, or clusters
network diagrams, including generation of node/edge characteristics based on metrics and groupings
Once we have you able to drive the car, let’s point the car to where you want to go. We’ll pick something happening right that minute and map the current Twitter traffic about it. We’ll cover:
uploading and analysing Twitter data
contents of uploaded Twitter data
analysis and display
We’ll finish by learning how to present your new knowledge to the world:
When we finish, you will be able to monitor the “Twitterverse” for reactions to your marketing, messaging, events or any other issue or news that may be causing reaction. You will be able to depict visually the web of Twitter messages and mentions that your event or message has generated and interpret its characteristics, identifying central players and distinct groups. You will also be able to look more deeply into the messages your have recorded, in order to understand more about what people are saying. And, you’ll be able to easily pick up where we left off to learn more about mapping other social media and networks.