I presented at a ‘BI without the BS’ event in London in November 2018. The idea was that there would be three tools and three players; Qlik, Tableau and Power BI, a judging panel, and a live audience of about 100 people. I represented Power BI and it was very clear that only a few people had seen it before.
As a data visualization person, I’m all about making things clear for people and that was why my story was much simpler and the facts were compelling, displayed in Power BI; I told a story which had a call to action.
My interpretation of the rules
My interpretation of the rules was that data storytelling was one of the main judging criteria. I had not seen the event as a product demo, and that’s why I emphasized the insights that Power BI gave me over knobs and levers that each tool can do. Product demos are easy, but not everyone can find insights in data.
Google Chief Economist Hal Varian predicted that data storytellers are the future over a decade ago. With data as the new oil, every company is seeking new ways to monetize their data. So my emphasis had been on data storytelling with a particular tool, but not trying to sell the tool itself as a demo. That’s my boxing ring to play in, and that’s the hard part of working with data.
An Equal Playing Ground for Games?
For my Power BI piece, my insights were all about the complexities in being a woman in gaming. My Power BI analysis showed that women earned just $1.8m in prize money in total, but the top male game winners earned $145m in total. See the tiny pink sliver? That’s the proportion that women earn in gaming competitions. If you’re thinking, that’s not a good dataviz to show, I can barely see the sliver – then you have missed the point. The point is, it is a tiny sliver. For colours, I have used Dark Orchid to represent female players, and Teal to represent male data throughout the visualization.
So there was a huge difference. In case you need the numbers:
So there is a huge disparity between male and female earnings. Is this because there are less women players? Apparently not. This chart shows that the gap between male and female players is narrowing:
In the data, I noted that the players were ranked from 1 to 100, for each gender. So I pitted the men and women together in terms of rank to show how the first ranked male player earned versus the first ranked female player. Here is the chart, in Power BI:
You can see that the girls’ earnings are practically flat, whereas the male earnings are vastly higher. The gender gap in pay is real, absolutely real.
I also noted that the lowest ranked player still earned more than double what the highest earning female player did. So the data showed lots of insights; it depended if you were willing to see things that made you uncomfortable.
Then, I wondered if there was a relationship between the number of tournaments played, and the prize money won. So, I used the male data here to see if a reasonable relationship could be inferred between the number of tournaments played, and the amount of prize money earned. If women are playing less tournaments, then naturally they will earn less. So how did that pan out?
The interesting thing was that the total number of tournaments played (on the X axis) didn’t seem to impact the amount of prize money earned. I’d have to do more analysis but you can see a vague relationship in the hexbin chart, but with a lot of outliers. I might come back and look at that another day, using R and Python or something.
Gaming in Real Life
So my piece was more about exploring the idea that there is no equal playing ground for women in gaming, and that’s certainly borne out by some of women’s experiences in the gaming world. Harassment for women in gaming can involve sexist insults or comments, death or rape threats, demanding sexual favors in exchange for virtual or real money, or even stalking. The GamerGate scandal tells you all you need to know about it, I suppose. Alternatively, you could look at Fat, Ugly or Slutty where women record instances of instances of sexism. Warning; it is not a pretty read. Or women hiding their identity online as a female, which is a safety measure that many women take. The most recent threat against female gamer Anita Sarkeesian was in Logan, Utah on October 15, 2014. She was scheduled to deliver a speech on a Wednesday evening until an anonymous email message arrived a day before, stating that there would be the deadliest school shooting in American history if the event was held. So don’t kid yourself that this isn’t real, and the impact means that many women are excluded from feeling that they can enter competitions in gaming.
Be Insights Driven, not Data Driven, and definitely not Tool Driven
When you analyze data, you bring your own personality and insights to analyzing data. I don’t believe that tools can solve problems; I believe that we have a lot of data, but no insight, information or wisdom unless we do something with the data. I don’t like the phrase data-driven; I prefer insights-driven. Qlik, Tableau or Power BI aren’t going to solve problems for you; they will just display data that hopefully brings about insights. The insights are yours and you can use each tool equally badly if you don’t have a story or a thread, or the data isn’t provoking an insight. We were all given the same data but we got very different results. That wasn’t down to the tool; it was down to the person driving the tool.
What I thought of the Tableau piece
I liked what Chris Love ( LinkedIn ¦ Twitter ) did; he clearly knows his stuff and it was nice to meet him in person. Funnily enough, we used to have the same boss when I had a boss (hello Tom Brown!).
I did find Chris Love’s visualization more interesting because he honed in on the journey of one player from the starting point to his success in winning a lot of money, and the journey was well displayed in Tableau. Chris had a good balance of context and detail, and for me, this was the data story telling piece. Here is the image below, credit to Laura Sandford:
What I thought of the Qlik piece
Nick Blewden ( LinkedIn, not on Twitter) is obviously fantastic at Qlikview and he did a good job of showcasing it. To be honest, I felt out of my depth here since it was a whizz tour of the product but since I’m not familiar with Qlik, I felt a bit bludgeoned with chart after chart and I couldn’t see a clear thread; it was information load as I tried to pick up the Qlik lingo as well as follow the story. I understand that Nick’s segment wasn’t aimed at beginners in Qlik and that’s ok with me; he only had five minutes to showcase what he’d done and he did a great job.
I am not familiar with the Qlik product set but a lot of the audience clearly were, and I could hear lots of mutters about ‘good to see he’s showing that feature’. So my perspective here is that of someone who does not know Qlik but who has expertise in Tableau and Power BI. I can look at Qlik another time, if I choose.
I felt I’d let Power BI down at that point because I had not gone down that route of doing a product demo and I feel really bad about that. I had gone for the analytics and insights part because I’d understood the rules that way, and the audience can see a Power BI demo anytime they like.
One reason for me to present at the event was that I’d seen it as an opportunity to learn more about Qlik from the session, but all I saw was chart after chart. For me, there were lots of business intelligence dashboard and that’s fine and I think that it was a good product demo.
So my lasting takeaway from the Qlik segment is this dashboard was interesting because it showed that it was quick to produce a lot of charts very quickly, but sometimes ‘less is more’. I’m a fan of Stephen Few and he talks about the importance of finding the signal in the noise, and having a ton of charts can simply mean more noise if they are not meaningful. Here is the image below, credit to Laura Sandford:
What I’d like to see next
I think I’d have preferred a larger, more mixed audience. A lot of people seemed to know one another already and I only knew one person in the audience. I’m not part of that community and it was nice to meet new people at the end.
Honestly, I’m not a fan of being shouted at by men I don’t know; it is really unpleasant. I think that the audience members should have the courtesy to refrain from shouting out during the performance. I was really put off with people shouting ‘Come on Qlik!’ and ‘Come on Tableau’ during the event. I didn’t hear a single voice for Power BI, not that it mattered; it really disrupted my thought flows to have people shouting when you’re trying to analyse data and I found it unsettling. Being at a live event isn’t like Gogglebox where the presenters can’t hear you.
So what did I think about the Power BI vs Tableau vs Qlik debate?
So what were my takeaways?
My call to action: be Insights Driven, not Data Driven, and definitely not Tool Driven.
According to the Qlik website ‘Deliver automated insight suggestions that help users see their data in new ways, auto-generating and prioritizing analytics and insights based on the overall data set and a user’s search criteria.’ Demystifying the marketing, it seems as if this means producing a ton of charts really quickly and if that’s what you’re looking for, it certainly did that. My overriding thought was that it can produce lots of charts but I really want to find meaning in charts, and I don’t measure meaning in charts by having as many charts as possible. I just got lost and I actually don’t think that’s good for Qlik.
For Tableau, I’d like to see Tableau become a real enterprise tool and it still feels like a cog in an enterprise wheel to me. I would not do any data prep in Tableau Prep although I do have experience in it; I’d want to use Power BI dataflows to clean data so that the data and the dataflows become part of the enterprise ecosystem.
I build big systems and I need to think big. When I’ve been working for customers, I’ve found it is easier to show ROI with Tableau and Power BI but it has taken longer for people to realize ROI with Qlik.
I am eternally confused by licensing and I find Tableau’s licensing simpler; Power BI and Qlik seem to be way more confusing to me. For Power BI, I always refer the customer back to their Microsoft reseller because they can figure it out for them.
My Power BI dashboard is here, for those of you who want to play with it:
Call to Action
I have put links, credits and sources here in case you want to play with the data.
