Tag Archives: data visualization

Big Data – Can’t ignore it?

Big data

2012 is almost over and I just realized that I have not yet posted a single entry about big data. Clearly a big mistake – right? Let’s see: Software vendors, media and industry analysts are all over the topic. If you listen to some of the messages, it seems that big data will create billions of jobs, solve all problems and will make us happier individuals. Really? Not really – at least in my humble opinion. It rather seems to me that big data fills a number of functions for a select group of people:

  • It provides analysts with a fresh and fancy-sounding topic
  • Media have something big to write about
  • BI companies obtain a ‘fresh’ marketing message
  • Professionals can have ‘smart’ discussions
  • Consultants can sell new assessment projects

Big data – really?

I do apologize for sounding so negative. But I have a hard time finding big value in this big data discussion. Please don’t get me wrong – I would be the last person to deny that there is a tremendous amount of value in big data. But it does not deserve the hype. On the contrary, I personally find that the current discussions ignore the fact that most of us do not have the skills to do big data. We need to get the foundation right and make sure that we can tame the ‘small data lion’ before we tackle the big data Gozzilla. Don’t believe me? Consider the following:

  • Spreadsheets are still the number one data analysis tool in most organizations.
  • Managers still argue about whose revenue and unit numbers are correct.
  • Knowledge workers have yet to learn how to make sense of even simple corporate data sets.
  • 3D pie charts are floating around boardrooms.
  • Companies spend over 6 months collecting and aggregating budgets only to find that a stupid formula mistake messed up the final report
  • Hardly any professional has ever read a book or attended a course about proper data analysis

Pie Chart

Here is the thing: Dealing with big data is a big challenge. It will require a lot more skills than most of us currently have (try finding meaning in gazillion TBs of data using a 3D pie chart!).

A big data problem

Earlier this year, I acquired a 36 megapixel camera. You can take some amazingly gorgeous photos with it. But it comes at a cost. Each photo consumes 65-75MB on my sad hard drive. Vacations now create a big data challenge for me. But guess what: this camera is anything but easy to handle. You have to really slow down and put 100% effort into each and every photo. 36MP have the ability to reveal every single flaw: The slightest camera shake is recorded & exposed. Minimal focus deviations that a small camera would not register, kill an otherwise solid photo. In other words: this big data camera requires big skills. And here is something else: The damn camera won’t help you create awesome photos. No, you still need to learn the basics such as composition, proper lighting etc.. That’s the hard stuff. But let me tell you this: If you know the basics, this big data camera certainly does some magic for you.burj khalifa

Big data – what’s next

Ok. That was my big data rant. I love data and analytics. No doubt – there is a tremendous amount of value we can gain from those new data sources. But let’s not forget that we need to learn the basics first. A Formula 1 driver learned his skills on the cart track. At the same time, there is a lot of information hidden in our ‘small data’ sources such as ERP, CRMs and historians. Let’s take a step back and put things into perspective. Big data is important but not THAT important.

With that: Thank your for following this blog. Happy holidays and see you next year!

Christoph

Related Posts:

Recommended reading for December

Recommended reading

December is always an interesting month. Analysts, software companies and journalists post a ton of predictions, reviews and opinions to celebrate the start of the new year. 2012 is not different. Here are a a few posts that I highly recommend reading.

Most influential visualizations

Tableau Software without a doubt knows a lot about data visualization techniques. That’s why I happily viewed one of their new presentations out on Slideshare. It’s called ‘The 5 most influential data visualizations of all time”. Some of the featured visualizations have been discussed by Stephen Few and Edward Tufte, but it’s well worth spending a few minutes reviewing and thinking about how they changed the course of time.

The statisticians at Fox News

Are you ready for some hilarious reading? Well, here it is. The good folks over at the Simply Statistics blog compiled a number of data visualizations that appeared on Fox News (don’t worry – this is NOT about politics). Most of the featured charts are flawed from a technical point of view, but it turns out that they do an excellent job of communicating the intended message (which can be very different from what the actual data says….). Read with a smile but don’t loose focus on the idea that there is an important message! Most of us strive to produce visualizations, dashboards and reports to provide an accurate portrait of reality. But we can also twist this around and do the opposite: confuse and mislead. You might also want to take a quick look at the comment section of that blog entry. That’s where the post starts getting political.

Simply statistics

One of the charts that is being discussed.

Nucleus Top Ten Predictions for 2013

Nucleus is one of those research houses that produces very interesting reports. I don’t always agree with the stuff that they write, but it is certainly amongst the most tangible in the industry. Their 2013 predictions don’t disappoint. And guess what – BI is on top of the list. The remaining predictions represent a mixture of different trends – most of which affect analytics to a certain degree. In any case, the free report is well worth a five minute investment. One of my favorite statements is: “It’s time to make sure HP has signed its organ donor card.” You can download the free report from the Nucleus website.

Nucleus predictions 2013

 

Related Posts:

Inspiration from Stephen Few

Greetings from San Francisco. I am back here to attend Osisoft’s vCampus developer conference. The conference kicked off with a true highlight: Stephen Few delivered one of the keynote presentations. Hopefully, all of you know Stephen and the awesome work he has done over the past years. Today’s presentation was content-rich and also very entertaining. There were a lot of smiling faces in the audience. I will write up a short summary of his messages over the weekend and share it on this blog.

Is this the information age?

Stephen Few started his presentation with a strong statement: We do not live in the information age…..yet. Instead, many of us are drowning in data and we struggle with making sense of the data. Part of the issue is that we are lacking ‘data-sensemaking’ skills. To highlight this point, Stephen Few showed a video. I had never seen it before. It’s funny but there is a strong message behind it: we do not understand how to deliver information properly.

Those concentric circles

Does your organization have a ‘concentric circle’ problem? I certainly know a lot of them. It’s time to change that. Take some time to evaluate whether your reports and dashboards are able to deliver real information.

Concentric circles

“Concentric circles” in the corporate world

 

Check back here in the next few days for a summary of Stephen Few’s presentation.

Related Posts:

A few thoughts about gauge charts

Gauge charts

A few days ago, I had a discussion about gauge charts. A colleague and I had reviewed a collection of operational dashboards. Some of them contained large sets of gauge charts. Those dashboards were the most ineffective. At the risk of repeating myself, here are some thoughts about gauge charts.

  • Gauge charts are not necessarily very effective at communicating information. Other chart types such as bar or bullet graphs are usually easier to read.
  • Gauge charts waste a lot of space. Dashboards should not require a user to scroll through its content. That would require them to use more working memory than we have. We therefore need to utilize the limited space we have in the most effective manner. Given the fact the gauges are not superior to other charts, why waste so much space.

Take a look at this example. Three of those bar charts fit into the space that is occupied by the gauge. Is the gauge more effective than the bar? I don’t think so. (By the way, the yellow lines indicate the range of the value.)

gauge chart

Two charts. Both convey the same information. Which one do you prefer?

Why then?

Most analytics professionals would probably agree with me that gauges are not that great. But why do we see them in so many dashboards then? I think the answer is pretty simple: People want to see them! The general level of knowledge about data visualization is still relatively low. Managers are therefore inclined to pick the chart types that look cool. Unfortunately, too many analytics professionals still shy away from pushing back on those requirements or they also lack knowledge. The lack of knowledge is also responsible that most software vendors feature gauges in their marketing materials (customers are asking for them).

Education

It’s up to us analytics professionals to educate business users about gauge charts. Let’s start that process today! Also, look at your dashboards. Where do you have the ability to clean them up?

 

Related Posts:

How to confuse and distract your audience with poor visualizations

Excuse me?

We often talk about how to best visualize data so that the audience can quickly discover the most important information in often complex data sets. But we cannot forget that it is also possible to achieve exactly the opposite effect: You can also leverage visualizations to distract and confuse people. As a matter of fact, it is possible to create visuals that completely hide important messages. Why would you do that? I guess if you want to hide bad news….right?

A bad example

The other day I received the 2011 spending report of the town that I live in. The text was quite dense and it included a ton of public sector terms that I did not understand. The core of the report, however, was centered around a graphic that outlines the detailed spending. Without further due, here it is.

Poor visualization

What’s wrong with this chart? Boy….pretty much everything: Extreme 3D, poor font choice (I can’t read it…), technical language and the colors… The sum of the parts is also not correct (as compared to the narrative). Percentages are not correct either (poor rounding practices). To be honest with you – when I saw this report I immediately got the impression that our town hall is trying to hide something. After some analysis I am still confused and not quite sure what to think about this.

To be fair, I believe that our mayor and his team are highly qualified. His approval ratings are extremely high for good reason. But this sort of communication does leave a bad taste in my mouth. It just makes you wonder….

A better approach

3D pie charts are never a good choice. The data above is quite simple and one could either leverage a standard sorted bar graph, a stacked bar chart or a waterfall graph. Really depends on your own personal preference. Here is an example:

Stacked Bar Chart

Related Posts:

An Easter Egg hunt with three charts

It’s that time of the year. Millions of kids are excited about hunting for Easter Eggs. Why not do the same here on the blog? Below are three charts. All of them are colored according to the season. But there are some problems with each one of the charts. Can spot them? Scroll down to see some comments….

Chart 1 – The Lollipop of Products

The Lollipop - Makes sense?

Chart 2 – The Pyramid of Deception

Pyramid Chart

The Pyramid - Admired for its shape and power

Chart 3 – Walk that line

Wrong Line Chart

The trend is your friend? Or maybe not?

Continue reading

Related Posts:

Why stacked line charts are useful

Stacked line charts

Stacked line charts are a great and yet simple tool. Here is why. We often run into a situation where we need to analyze data with different units of measure. Think about  a classic but yet simple situation: Vital company data such as revenue, margin % and expenses is used to obtain insights about the past and current performance . One could dismiss this as an easy task and simply review a standard table. But raw data is really tough to analyze. Detecting trends and patterns quickly is almost impossible. Especially with regular data sets that span multiple organizational units

Analysis

Raw data is hard to analyze. Even simple data sets as this one here.

The other option would be to stick the data into a traditional line chart. But this won’t work in many cases for two obvious reasons:

  • The units of measure are different (Revenue ($), Margin (%), Headcount (#), Volume (#), etc..)
  • The units of measure have large differences (example: Revenue is measured in millions, travel cost in thousands)

Both cases result in a pretty much useless chart. You can see a fine example right below:

bad line chart

An almost useless chart - What are the margins again?

For data sets containing just two different units of measure, we could alternatively consider a dual axis graph. But I personally find them distracting and many casual users get confused. This is where stacked line charts come in handy.

The power of stacked line charts

Stacked line charts are basically a bunch of line charts that we stack. Why is that useful? Well, take a look:

Stacked line chart

A stacked line chart - A better option

The stacked line charts allows us to easily identify and compare the trends and patterns in our data. Using this stack is fairly easy. We just have to keep in mind that the units of measure or the scale is different in each one of the line charts. But that should be obvious.

Your analysis

Generating these stacked line charts is really easy with personal analytics tools like Cognos Insight. Spreadsheets typically required us to generate various different charts and to align them manually.

If you haven’t use them before, get started today! Stacked line charts are very powerful, yet easy to use.

Related Posts:

Watch that chart aspect ratio!

The chart aspect ratio

The other day I reviewed a dashboard. It looked great. But there was a chart on the bottom that just did not make any sense. It was way too long and stretched out. As a result, it was very difficult to use it appropriately. And that reminded me: We have to watch out for the chart aspect ratio.

The basic idea

Wikipedia defines the aspect ratio as follows: “The aspect ratio of an image describes the proportional relationship between its width and its height.” It’s as simple as that. We get confronted with the aspect ration when we purchase a TV or computer monitor or when we work with photographs. Does the aspect ratio matter? Oh, yeah it does! Take a look at the two photographs below. The first one uses the common HD 16:9 ratio. I cropped the second one down to a square format (1:1). Do you see the difference in the overall impression of the photo?

Square Aspect Ratio

16:9 (HD) Aspect Ratio: Can you feel the wide and open ocean?

16:9 Aspect Ratio

Square Aspect Ratio: Not that great. The boat has too much visual weight and the ocean does not seem vast and wide.

 Your charts

The aspect ratio does matter for charts as well. We have to watch out for that when we create reports and dashboards or when we perform ad-hoc analysis. Not every chart aspect ratio works equally well. Take a look at the two examples below. Both of these charts have problems:

It is difficult to make sense of the data. It is too flat.

Chart Aspect Ratio

The peaks are very pronounced.

The first chart is definitely too flat – it is very difficult to analyze it. The second one is probably a bit too dense. The peaks are extremely pronounced and it would be easy to come to wrong conclusions.

A better approach

What is the idea aspect ratio then? Hard to say. It is typically a good idea to use a ratio that is wider than it is tall (2:1 or something like that). But it depends on what you want to show. From my point of view, it makes sense to experiment a little bit. I have noticed that some visualization experts have issues advice but I have found it to be very academic and hard to implement. To stick with the example from above, I did re-size the graph a bit and finally settled on this chart aspect ratio:

Better Aspect Ratio

This aspect ratio seems to work best for this data

Your dashboards & reports

Pay attention to the chart aspect ratio. Only because there is some space left in a dashboard does not mean we can or should stick a certain graph in there. The chart aspect ratio does matter quite a bit as we have just seen in these simple examples. Also, try experimenting with different chart aspect ratios when you perform analysis. Resizing charts with personal analytics tools such as Cognos Insight is really simple.

 

Related Posts:

Freedom to think?

Change that viewpoint

Last summer I participated in a Bavarian wedding.

As a photographer I was really excited to see three traditional alphorn players. The early results looked good on the camera monitor (left photo). At that point I was tempted to pack up and celebrate with my friends. But I resisted and began to experiment with different viewpoints. The final shot ended up as my personal favorite (photograph on the right). Same scene, different perspective. Changing viewpoints paid off.

Alphorn

Business Analytics and Viewpoints

Changing our viewpoint is especially critical for Business Analytics. Continue reading

Related Posts:

Visualize This! A book review

Visualize this!

Visualization of data is one of the hottest topics these days. No matter where I go, people are taking a huge interest in it. Infographics are floating the Internet, for example. Companies are looking to refine their dashboards with better visuals. This was also apparent at the Gartner BI Summit earlier this week.

Despite the tremendous attention, there are only a few good books about this topic in the market. One of them is Nathan Yau’s title Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. This week, I was able to finally read it all the way through. Did I enjoy reading it? Yes and no.

visualize this

Great concepts

Yau does a fine job with engaging the reader in the first part of the book. He explains a number of important fundamentals of visualization. This includes a process that he suggests people should follow:

  1. Get your data
  2. Ask a question (what do you want to know about it?)
  3. Choose your visualization tools
  4. Explore the data (look for trends, patterns, differences, etc.)
  5. Tell the story and design the visual

There is a lot of relevant information for business analytics professionals in this section. I particularly like that Yau urges his readers to clearly figure out what story they want to tell by visualizing data. This is often forgotten in the design of a dashboard (e.g. do I use a line-chart to show the trend, or do I use a bar chart to show the variances?)

“Approach visualization as if you were telling a story. What kind of story are you trying to tell? Is it a report, or is it a novel? Do you want to convince people that action is necessary?” Nathan Yau

The other chapters

The remaining chapters of the book contain valuable content as well. The author covers topics such as handling data and picking tools for building charts. Several chapters are dedicated towards describing how to best visualize certain problems (e.g. patterns, proportions, spatial relationships, etc.). Each section provides plenty of examples and some good ideas. I enjoyed working through this. But I do have to say that the content isn’t nearly as deep as let’s say Stephen Few’s material.

A good book for BI professionals?

So far so good. There is just one thing that you should know: Many chapters are also full of technical instructions that teach you how to build graphs and charts in the open source package R along with Adobe Illustrator. There is a lot of code in the book. Technical folks might enjoy this. But it is not my cup of tea and most BI professionals will hopefully build their charts using the corporate BI platform. To be honest, I went ahead and skipped those pages.

Visualize this!

Nathan Yau’s book Visualize this! is definitely a good book. I learned a few things here and there and took ample notes. It is also entertaining.  However, one has to understand that this is not necessarily a book dedicated towards BI professionals. Rather, this is a book for people who are looking to build infographics and other standalone visualizations. Nevertheless, you can tell that Nathan Yau is passionate about it and he inspired me to hone my skills. If you are looking for a deeper and more business oriented read, I would rather recommend the books by Stephen Few and Edward Tufte.

Related Posts: