Understanding how our brains interpret the world can help us become better storytellers. That’s where neuroscience comes in. The field of neuroscience covers anything that studies the nervous system, from studies on nerve endings, data processing, and even complex social behaviors like economics.
Go to a tech conference, and you need only to look at the restroom lines to know that it’s a man’s game. Men often have a long wait while women can march right in.
Things fare a bit better in the data industry. Go to the Tableau Conference, for example, and women, too, have to wait in line. Women in the data industry share anecdotes of a slightly better-balanced field (though, ironically, there’s no data to support this).
And that, in short, is why you might consider hosting a Data + Women meetup.
A little over a year ago, I started playing bass for a band called Golden Idols. Aside from my extreme bass riffage and overt super-cool-rockstar energy, the band was excited for me to join and bring the skills I had learned over the past couple of years as a marketer. As a result, I got put in charge of the social media efforts of the band.
This is a little tip that started out with a “Tableau doesn’t do that” and then an “Ooh…it does…that’s so cool!”
Here’s the problem: In a single-measure table, I want the name of the measure column as a header. In this worksheet, using the coffee chain data, I want the header “sales” to show up on top of the sales column:
This is an analysis of Twitter hashtags over the weekend following the terrorist attacks in Paris. I chose to try to tell the story with Twitter's data. I used the website talkwalker.com to get the data. The data set is aggregated by the hour starting on Friday, Nov. 13.
“Shut up about the y-axis. It shouldn’t always start at zero,” reads a Vox.com headline.
"There is no evidence that anybody has been converted by a pie chart."
So said Martin Palmer, secretary general of the Alliance of Religions and Conservation, on BBC’s Beyond Belief in June.
He went on to say, "People are converted by stories, by narrative, by emotion, by an appeal to the heart."
This was a discussion about climate change and the Pope’s encyclical on the issue. Palmer's opinion is a serious indictment against those of us who try to use data to make change. As Palmer states, data analysis often doesn’t drive the change we hope it will.
Scatter plots are my favorite visualization type, hands down. From my very first interactive data graphic about The Great One to the most recent visualization below on major league pitchers, I’ve learned a great deal from these Cartesian classics over the years. In this post I’ll show you how to make them even better than the standard ones in Tableau.
Recently at work, my colleagues and I were introduced to a new map type that one of our users saw on FiveThirtyEight—tile grid maps! I quickly searched Google images to see what she was talking about. Immediately we knew this was possible in Tableau, and I'm excited to share the steps.
The National Football League has a huge fan base that pledges to 32 different teams. In order to serve each team and its fans, the league needs to know what each one wants and needs. In other words, the league has to make sense of data—and lots of it.
The NFL collects data from traditional websites, mobile websites, and mobile apps. To make sense of the numbers, the teams had to sift through multiple spreadsheets and a dizzying array of reports. The league knew there was a better way.
Years ago no one talked about “storytelling” in a business sense. In the last 18 months, I’ve had a number of clients ask about using storytelling techniques. A lot of the buzz is coming from their love of Tableau, and wanting to know what the Story Points capability brought to them. Storytelling is not something used just for getting a 5-year-old excited. A simple way to think of storytelling is to just call it a presentation. Anytime you do a presentation, you need to use good storytelling techniques.
With the rise of low-cost sensors, connectivity everywhere, and our fast-growing volume of data, the Internet of Things is likely to reshape the world as we know it. The possibilities are immense, but so are the challenges. Making the IoT work for the masses is more of a data challenge than a problem of things. We need to extract the data from devices then figure out what it all means.
Which Beatle was the muse behind your favorite album?
Find the answer using this viz by Mike Moore. Mike used data based on numerous interviews with the Beatles.
Wheaton Industries started as a family-owned business 126 years ago. It has since grown into a worldwide enterprise that makes glass and plastic containers for the life-science and healthcare markets.
For many years, analytics at Wheaton involved a using a highlighter pen on dot matrix paper reports. Wheaton’s sales team used to feel like they were on an island, says Chris Gildea, vice president of North American sales.
We live in a world awash with data. From sensor data to website data, to fitness data, nearly every aspect of our lives is quantified. And digging into the numbers helps us better understand ourselves, our neighbors, and our world.
For organizations, this can yield a huge competitive advantage—if they can see and understand their data. And that’s why many are adopting a culture of self-service analytics.
When it comes to communicating data, I am a big proponent of using preattentive attributes—elements like color, size, and position on page—to focus your audience’s attention on the most important parts of your data. These are visual cues that ease the processing of the information. When done well, there should be no question on the part of your audience when it comes to what is important or where they should focus their attention—it is obvious.
If you’re an adult data enthusiast, then you know what it feels like to uncover a powerful insight within your data. But this aha moment doesn’t have to be restricted to grownups.
So how do you introduce kids with no data background into the data world? Give them that same aha experience, of course.
There’s no question that mobile is a critical part of Tableau's mission to help people see and understand their data. That’s why we shipped our first mobile app more than four years ago with Tableau 6.1. We knew our approach had to be different from those of traditional analytics solutions. We focused on fast, easy, beautiful creation and delivery. And we didn't require a developer or a special server.