Trump’s Chances – Redesign of The New York Times’s Infografic

In the recent update of The New York Times's article Who Will Be President? the authors used an interesting and a slightly controversial infografic, consisting of 16 sparklines. The graphic depicts the trends of Donald Trump's winning probabilities in the states, where his chances have increased most over the last two weeks.

Unfortunately, the visualization fails to convey a proper picture of the trends due to inconsistent scaling of charts, proving once more, that the correct scaling is still one of the hardest problems in data visualization. We'll present 3 alternative solutions that allow the readers to properly assess and compare changes across the states.

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Designing Financial Statements for Non-Profits & Foundations – The Gates Foundation example

This time we'll take a deep dive into the 2014 annual report of Bill & Melinda Gates Foundation to find out if data visualization can help explain their consolidated financial statements. As Stephanie Evergreen pointed out in her intriguing article, there's a lot of room for improvement in annual reports of non-profits and foundations (to put it mildly). Data visualization in annual reports is far from being efficient and clear. Many times it's just non-existent. 

Stephanie's got an excellent point. However, when observing her proposed visuals and especially when faced with the extreme ranges of values in the financial statement of Bill & Melinda Gates Foundation, I thought it's time to add some more 'meat' to this topic.

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How to visualize trends for multiple markets, products, etc.

Recently, my attention was drawn to an interesting analysis of The Hottest Startup Sectors In 2016, written by Tomasz Tunguz. It shows the trend of investments into 16 major startup markets and tries to expose the gap between seed and Series A investment dollars.

The arrangement of charts into a "small multiples" chart matrix is an excellent idea. However, when you start drawing conclusions from the visual representation, you may arrive at some seriously false conclusions. Let's take a closer look:

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Aggregate media usage (Nielsen)

Why are some charts difficult to understand?

Charts should provide a clear and practically immediate insight into the underlying dataset. Especially if we're talking about one single chart, created from a tiny, almost trivial dataset. If we cannot achieve that, how will we tackle the complexity of our business and social environment in the age of big data?

Let's take the following example of media usage from the Comparable Metrics Report Q2 2015 by Nielsen:

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Management report Hemofarm 2

The 3 steps to implementing management reports in a pharmaceutical company

Marko Devrnja

Mr. Marko Devrnja, Hemofarm

This is a guest post by Darko Vlajković, a consultant at MCB. See more about MCB at the end of the post.

We had an opportunity to work with Sales & Marketing team in Serbian pharmaceutical company Hemofarm, that operates in more than 30 countries on 3 continents and has approximately 2.500 employees. The goal of the project was to make management reports more transparent, visual and automated. The end result was reports that top management could analyze quickly and easily and make the right decisions based on them.

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Young adults’ living conditions getting worse – a redesign of The Guardian Datablog’s visuals

As announced yesterday by The Guardian Datablog, more and more young people (aged 18-29) live at home with their parents. On average 48% of young people in EU lived with their parents in 2011. This percentage varies significantly by EU member states, reaching 85% in Malta and Slovenia and growing +36 percentage points in Hungary between years 2007 and 2011. Even more concerning is the fact that in the majority of EU countries the proportion of young people experiencing high deprivation (stated that they cannot afford to keep their house warm or buy new clothes instead of second-hand) increased dramatically.

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Happy Valentine’s Day! But hey, where is the romance?

It is Valentine's Day today, so we created a quick analysis with our Zebra BI to see if data on Valentine's Day spending and gifts conveys any important messages. It turns out it does.

More spending, less time for romance?

According to the data from BIGinsight, people give 8% less Valentine's cards and take their partners for an evening out 9% less than in 2007. On the other hand, we buy more candy, more jewelry, more clothing and give 4% more gift cards for shopping. Hey, where's the romance gone?

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