Basic Data Analytics Tactics
Lesson 16 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
Basic Data Analytics Tactics
Lesson 16 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
Lessons
Introduction
1Class Introduction
03:29 2Do The Exercises
00:37 3Communication Challenges and Solutions
05:20 4Exercise: 4X4 Model
04:31 5Exercise Solution: 4X4 Model
03:25 6Introduction - Quiz
Thinking Like a Communicator
The Power of Story
06:48 8Six Ways to Tap Into Your Inner Storyteller
12:32 9The Importance of Understanding Your Audience
03:42 10How to Understand Your Audience
04:35 11How to Embrace Emotion (to review)
04:38 12How to Tap Into Your Inherent Creativity
05:55 13Exercise: An Emotional Story
01:29 14Exercise Solution: An Emotional Story
01:12 15Thinking Like a Communicator - Quiz
Telling Data Stories
16Basic Data Analytics Tactics
08:54 17Basic Journalism Tactics
04:56 18Defining Your Story
05:37 19Sketching and Storyboarding
07:05 20Use Your Words
04:20 21Telling Data Stories - Quiz
Essential Design Principles
22The Power of Visuals
07:44 23How to Pick the Right Chart for Your Data
05:19 24Exercise: Chart Selection
06:27 25Exercise: Visualization
02:59 26Basic Chart Designs Principles
08:21 27Research Driven Design Principles
06:27 28Exercise: A Data Story
03:50 29Essential Design Principles - Quiz
And Now What?
30Great Data Stories for Your Inspiration
05:53 31Tips and Tricks
03:53 32How to Sell Data Storytelling Services
03:56 33A Conversation Guide for Talking to Prospects About Data Storytelling Projects
05:30 34Course Summary
02:48Final Quiz
35Final Quiz
Lesson Info
Basic Data Analytics Tactics
in this section of the course. We're going to cover a bunch of hands on tactics to get from data to story from basic data analysis practices in this lesson to thinking like a journalist and then defining and story boarding something that you can execute. Data analysis is an art. As much as a science you get out of it what you put into it. But there's a lot of gray area in all of it. There's a great tradition called Makeover Monday which you can find at this U. R. L. It's organized by Andy Kriebel who runs the visit his blog and Andy kat Grieve of Tableau. The basic ideas every week they look at an infographic or visualization in the wild, they share the data set and then people following the hashtag are supposed to download the data and do something different with it. It's not about critiquing the original. Just trying something new and different. As I was putting this course together, I decided to take a look at one and this is the post from the week I was looking at. It's about the m...
ilitarization of the Middle East. So there's a bunch of data in this post. So as I scroll down, the first thing I see is arms trading around the world and I can see exports and imports and the size of the bubble tells me how much is exported and or imported in or out of each country. I see a little spark line little mini line charts showing the growth or decrease of imports in europe and the Middle East in this case some country specific data. And as I scroll down and down and down there's a lot of data here to look at bar charts with line charts showing, you know the volume of arms trades across the entire time period in the data set. And then it focuses more narrowly on the Middle East and some other things. Long story short, it's a really interesting data story. Well worth looking at and really interesting data set to work with. So the basic idea for makeover monday is just to try something different and you don't have to use every bit of the data. Um you're supposed to just do something quick, take an hour or so uh and really to sort of take that data. And the work that's been done is some sort of initial guidelines. So what I did is I went and of course I downloaded the Excel spreadsheet from the website to make up for monday site which is right here as you can see and I made some adjustments to it. So I want to show you that one. So the first thing I did is I filtered only by imports because if we're talking about the militarization of the Middle East, we're talking about arms coming to the Middle East, we're not, we don't really care about the arms that they're exporting out. And then I also filtered only by region. So we're only looking at those countries in the Middle East which of course makes sense. And then I can see all the data and as I start scrolling over um The very first thing I tend to do in a project like this is generate a chart. I'm a very visual person and in many cases looking at a visual of the data is a really helpful way of looking at it. Um When I generated this chart though, what I first saw was in addition to kind of a hot mess, which we'll talk about later in the chorus. Um I saw sort of a contradiction or at least I'm not quite sure if the original infographic that we looked at looked at is necessarily correct. I don't know that there is a militarization of the Middle East going on. I see one or two countries that are definitely going up but the rest, I'm not quite sure. So the next thing I did is I generate line charts for every single one of the country's so I could look at them individually. And that really started to show me some pretty interesting things. For instance, I can see that countries like Jordan's had a huge spike in arms imports back in, I don't know the 70s, 80s, 90s and most cases, most of these countries and then has really mostly come down over the many years since. And so looking at this data is starting to tell me something, I'm not quite sure what yet, but something is going on here, You'll notice in these line charts that there are two lines. Um I also added the five year moving average. Um So I see not just these, you know, huge spikes in the data but I see sort of more normalized um what the data really looks like. So the five year moving, moving average and Excel, it's pretty easy to add. Um We're not gonna go over how to do that here. You can find plenty of places online to learn how to do this stuff and excel. But you know, I'm starting to see more what the shapes of the lines look like over time and not just the dramatic spikes now if I go and Excel and I actually want to hide a lot of the data here because really I'm most interested in the more recent years that that original infographic was focusing in on 2006 going forward I believe if I remember correctly. So I'm actually going to hide all of the columns in the spreadsheet Um all the way up to. And including 2000 and so if I just select them all and right click or control click and just say hide now I have a lot less data to deal with. And you'll also notice conveniently that my little line charts actually updated so I can see just that bit of data that I really want to look at. So the next thing I did looking at this, I'm thinking okay, maybe they're growing, Maybe they're not maybe sort of spiking and falling and spiking and falling population size is sort of part of this conversation I think so I actually went and fetched a bunch of population data. I actually got population statistics from the World Bank. So for each country here, I have the populations of those countries for each of these years and so you'll notice up here in the spreadsheet, I have this and then I created a calculation. I said, okay, what is the population change over that time? I thought I might do something with that data ended up not doing anything with that. And then I looked at the arms spending arms imports, per capita, maybe even small countries are spending way more than they should be on a population basis. And then I charted that now this revealed in some cases even less than the original data. So I ended up not using this, not really going anywhere with it, but it was worth taking a look at. Finally I created this chart Because if you remember in the original infographic, they were looking really at 2006-2010 versus 2011-2016, saying that there was a major spike after September and so I just plotted those three years here. It's labeled incorrectly on this chart but essentially this is 2000 and 6 to 2000 and 10 to 2016. And what I very clearly see here, even though it's hard to tell because of the color scheme is that Saudi Arabia had a huge spike and was always growing its arms imports across this entire time period. But again, all the rest of the countries, it's a much more muddled picture in the end, the main story really seems to be about Saudi Arabia and its neighbors in the gulf. For those who don't know, the gulf countries are across the Persian gulf from Iran, the two dominant powers in the Middle East are Iran and Saudi Arabia. Saudi Arabia dominates the gulf and Iran has influenced in plenty of other areas. Those gulf countries have always felt threatened by Iran and vice versa. So while a post-9- world and in its stability in Iraq and Syria and ISIS are definitely part of the equation like the original infographic was talking about the story is much more complex. The data reveals a much more nuanced story that could really be investigated while there is growth in arms imports outside of the gulf. In Egypt for instance, there really is a much narrower regional story at play here. But this initial analysis I've done is only the beginning. I want to look more closely at percentage change of imports over time for those countries. And this is only about imports right since the Iranian revolution, there have been practically no imports in Iran because of the embargo and its isolation from the west. They're creating their own weapons. One assumes this data doesn't really tell the entire story. It would be really interesting to see any data about Iran For that matter. How much has the United States or the UK or France been militarizing for the past 10 years? Just because were net exporters doesn't mean we're not militarizing just as much as some of these other countries. The main point is that you have to dig into the data. Look at it from different directions. Try varied views. Look visually, look at the numbers, look at real values. Look at percentage changes. Look at outside data like I did with the world bank data. Long story short data analysis is about thinking like an explorer. Keep an open mind. Be skeptical of everything. Your job is to poke at things and find inconsistencies. Assume that you're not seeing the whole picture. Look at the data from as many angles as possible. Eventually you'll start to see some patterns emerging for instance, no matter how many different ways you look at Saudi Arabia, it dominates the picture every time. Whereas some other countries like Qatar aren't really quite so clear cut. So focusing in on Saudi definitely feels legit and worth further exploration to me. So I would encourage you to do this if you want some practice by the way, I never got to do this makeover monday project because I was too busy putting this course together. But I do plan to do some in the future and you should, too. It's great practice in the next video, we'll run through some basic journalism tactics because thinking like a journalist is thinking like a data storyteller.
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