How to Read a Sankey Visualization

n dimensions + 1 metric

Shows the distribution of a metric on several dimensions, with the value of each dimension’s distribution shown on the next dimension.

Example : It’s possible to distribute the “visits” metric on a “types of visitors” dimension where the values could be “new” and “known”, then distribute the “new” and “known” on a dimension “sex” between male and female.

For Example: Let's say you want to track the entire journey of your visitors. Which channels do they come from? Which pages do they land and leave on?

You can clearly see that the majority of your visitors are new.

Sankey New visitors

Most of your new visitors come directly to your website via url, but a significant portion also come from referrals.

sankey referral

Your known visitors mostly come from organic search.

Sankey organic search

All of your organic search visitors accessed your website from google.com, and most of your referred viewers come from designmodo.com, designfestival.com or forum.vietdesigner.net.

sankey google

sankey designmodo

What about landing pages?

Direct and organic search visitors land on /the-company, /the-product or /home pages.

sankey companyUh oh...your referrals are landing on your /404 page.

sankey 404 You must have removed a page from your website which was referred to by an external link. Something must be done about your 404 page and your /511 page because people land on it and leave without ever finding your home page.

Is this the journey you had in mind for your visitors?

In order to play around some more with Sankey Visualizations you can head over to the visualization lair at Captaindash.com.

How to Read a Treemap Visualization

1 dimension (hierarchical or not) + 1 metric

A Treemap visualization represents a hierarchical dimension by encoding a metric on each node of the hierarchy.

Example : The hierarchical dimension of geography. On the first level, we can see the distribution of the metric between continents. We can then explore a continent to see the distribution between countries, etc.

Let’s say you want to check out where your visitors are located.

 

 

Treemap Captain Dash 1

Let's Analyze A Bit

At a mere glance, we can see that nearly have of your visitors are in Europe, a quarter in the Americas, the remainder in Asia, and but a few in Oceania and Africa. The “Explore” button gives us a closer look at Europe, revealing that half of those visitors are in the West and the rest are split evenly between North, East, and South.

Treemap Captain Dash 2

Another “Explore” click and we see that more than half of your Western Europe visitors are in France.

Treemap Captain Dash 3

A look at the Americas reveals that the United States accounts for 86% of viewers on the continent.

Treemap Captain Dash 4

Is that where you should open your new office?

In order to play around some more with Treemap visualizations you can head over to the visualization lair at Captaindash.com.

How to read Leaderboards

Leaderboard

The leaderboard displays a metric over a dimension in a way that allows you to easily categorize each dimension value’s “performance” in terms of the metric value.

Leaderboard Visualization Captain dash

In the example above, we can see the amount of revenue distributed over different dimension values (Points of sales). The dimension values are displayed in descending order, from the highest metric value to the lowest which allows us to “stack them” against each other. Travelling down the visualization, we can see that Shanghai is the point of sale selling more, followed by Berlin, then New York, etc.

The general statistics displayed allow us to determine the significance of each dimension value by comparing it to the Total and Average revenue per point of sale.

In order to play around some more with leaderboards you can head over to the visualization lair at Captaindash.com.

Two dimensional Leaderboards

These three different leaderboards essentially offer a different view depending upon how you wish to present your data.

Grouped Leaderboard

Grouped Leaderboard Captain Dash

 

 

The Grouped Leaderboard further segments the revenue by town into “Point of Sale A” and “Point of Sale B”, which allows for a more specific breakdown of information. The two values are grouped together vertically with the superior value appearing first.

Stacked Leaderboard

Stacked Leaderboard Visualization Captain Dash

 

The Stacked Leaderboard combines the two values together, which grants a view of each metric value as a “part of the whole.”

Superimposed Leaderboard

Superimposed Leaderboard Visualization Captain Dash

 

The Superimposed leaderboard displays the total amount of sales on a bar, with a specific segment highlighted for identification. In this case, we can visually pick out the “online sales” from the bar of total sales.

In order to play around some more with two dimensional leaderboards you can head over to the visualization lair at Captaindash.com.

How to Read Stacked and Bar & Line Graphs

GROUPED/STACKED BARS

These add a dimension to the bar chart, represented by a group of bars or one « cut » bar on the dimension of the horizontal axis.

Stacked mode allows you to effectively observe the evolution of the sum of elements of a dimension, over the dimension of the x-axis (example: time), and gives you an idea of the distribution of elements within that dimension.

Grouped mode compares the parallel evolutions of each element of the dimension, which is shown by a group of bars.

grouped:stacked bars Captain Dash

Let's say you want to split your visits over time by type of referral. You want to see on a day-to-day basis if your visits are direct from search engines or from other websites to which your website is linked.

At first glance it’s clear that visits from search engines vary little over time, as opposed to direct visits or referrals, which vary quite a bit more and display an almost parallel evolution.

If we switch to stacked mode, we can see that the proportion between direct visits and referrals is regular over time.

What does this mean? That your visitors already know how to access your website, whether it be by typing the URL or because they know where to find a link?

In order to play around some more with grouped/stacked bars you can head over to the visualization lair at Captaindash.com.

 

BAR & LINE GRAPHS

The bar & line visualization grants the comparison of many different elements of the same dimension on two common metrics and is effective in exhibiting a time evolution. This method allows you to see the correlation between two metrics.

bar & line captain dash

Let's say you want to see if an ad campaign is effectively translating to greater web traffic and a higher number of visitors viewing your content. Adding a line representing your website bounce rate shows you whether your paid visits are efficient or if your visitors just leave your website as soon as they arrive.

At a glance, we can see that even if your paid visits vary dramatically, your bounce rate remains relatively consistent over time. You can still see, however, that the slight curve in the bounce rate correlates to the evolution of visits over time. The higher the amount of paid visits, the higher the bounce rate (and vice versa).

So is your campaign worth it? Oh, and keep an eye on your bounce rate...it seems to be increasing over time.

In order to play around some more with bars & line graphs you can head over to the visualization lair at Captaindash.com.

8 tips for building a beautiful infographic

DNxvj The latest buzz in the data universe is that infographics are the hottest new way to display information. More visual than simple text yet more informative than numbers and charts, they’re the new way of show-and-tell in this data-driven world.

 

An infographic can serve many purposes. It can educate or inform your audience, promote your business, or simply tell a story. The beauty of it lies in the fact that it can communicate a message simply and effectively through a combination of data and images.

If your goal is to convince your reader to not to drink and drive, you can simply present information that reveals the consequences and dangers through statistics and powerful imagery.

If you want to promote your company, you can detail information and statistics that make it clear that your product will give x and y benefits for your consumer then present statistics that support the effectiveness of your product.

Your company has a lot to benefit from creating infographics for use as promotional material or disseminating them through your social media platforms. That being said, it’s important that you follow certain rules of thumb in designing and creating the content of your infographic in order to ensure that it accurately and compellingly conveys the intended message to your viewers.

Here are a few tips to ensure that your next infographic is engaging, fun, informative and shareable.

First impressions are important: your viewer’s initial impression means everything. Don’t scare them away with an intimidating, jam-packed space full of letters and numbers. Your infographic should have specific images or words on it that pop in order to reel in potential readers.

Create a path down the page: decide on a path that you want your viewers’ eyes to follow as they read your infographic down the page. Pre-designate the specific path and then put in the information and images afterward in the order that you want your viewer to read them. Try to avoid a straight vertical path and rather opt for a slight zig-zag path, which is much more natural for the eyes to follow.

Avoid a white background: a white background screams corporate monotony. I recommend a light, neutral background color to help meld the text and images together and make the entire thing more aesthetically pleasing.

A fun yet clear font: it can be easy to become too committed to a specific theme. A letters-dripping-blood theme may seem like a good idea around Halloween, or perhaps an intricate calligraphy typography seems appropriate for an infographic about Victorian England. Sadly clarity must trump creativity when it comes to the font. Your text content is just as important as your imagery

Keep imagery simple and stylized: Remember, the focus of your infographic is meant to be on the meaning behind the images and numbers.  You won’t get points for realistic pictures of a jumble of overly bright images; keep the bright colors only for things that you want to make pop, and keep images stylized and simple.

Creative graphs: The typical line and bar graphs that you’d find on Excel are boring and tired. If excel can make your graphs then what are you for? Keep graphs simple and intuitive to maximize viewer understanding, but shy away from generic graphs. Keep your visualization tools fun and fresh.

Human images tend to make the best impression: Studies have shown that abstract graphs are less memorable than graphs that resemble known objects. Try to anchor your visualizations around some sort of human-familiar object. For example, if you’re making a pie chart, turn the pie into a familiar circular object like a soccer ball or a clock.

Keep text to a minimum: Your infographic isn’t a list of statistics- it’s a form of visualization. Make sure that the text complements the visualizations and vice versa. .

It certainly helps to do a little research on your own as well. Check out an infographic-rich website like for inspiration like informationisbeautiful.net.

 

Over and out, The Captain

Infographic Vs. Data Visualization: Definition and Differences

DataVisField_43 Last year, the word “infographic” was tweeted 56,756 times. Publishers who use infographics grow 12% more in traffic than those who don't.

 

Wasn't that boring? By itself, that set of quantitative facts is no more than text, but when put in the context of a visualization, it's been proven that viewer understanding and engagement skyrockets. This discovery has driven a wave of people scrambling to contextualize their messages in visualization form, most commonly as an infographic or a "data visualization." The line between data visualizations and infographics is thin when they're both describing quantitative data, yet we must define the two in order to decide which one will be more effective in communicating a specific message.

An infographic is typically a data-rich storytelling tool that educates and informs the viewer in a fun and interesting way. It tends to read out a bit like an essay, beginning with a clear main topic in mind and then followed by a specific path of information meant to construct a supporting argument. Although an infographic generally does not aim to distort the truth it often tends to simply because of its persuasive nature. It doesn’t adhere to any sort of implicit contract of objectivity and rather presents data that will support its purpose while potentially omitting the facts that won’t.

By contrast, a data visualization is more objective and simply presents data, thus allowing the viewer to explore and interact with the information and form their own conclusion. However, the opportunity still exists to manipulate the information in order to emphasize a specific data correlation or trend. It’s possible to choose specific dimensions and metrics in creating your visualization that will emphasize a certain message in order to influence the viewer’s opinion on the subject.

It seems that the key difference lies in the creation process. The construction of an infographic begins with the end and pieces itself together backward, whereas a data visualization starts with the building blocks and lets the viewer explore the data themselves to find their own conclusion.

Here’s an author’s interesting take on the difference between an infographic and a data visualization. He’s created a half-and-half hybrid that helps highlight the differences between the two: http://www.nytimes.com/interactive/2014/03/15/business/higher-income-longer-lives.html

 

 

Ancient Greek Concept of Spatial Memory Helps to Visualize Data

  Raphael_School_of_Athens

Happy Friday everyone! In honor of the weekend, let’s take a little vacation 2700 years into the past to the great land of Zeus and olives: The Ancient Greek Empire!

The ancient Greeks essentially laid the foundation of the modern Western world, and it’s them that we have to thank for the modern adoptions of concepts in the realms of philosophy, astronomy, mathematics, architecture, science, and spanakopita.

The Greeks held the highest regard for the development of the intellect and occupied much of their time with shows of rhetoric, poetry, and wit. They were great explorers of the human psyche, notably in the realm of memory. They developed the method of Ioci, which at it’s core is simply a mnemonic device, but can actually teach us a lot about the power of spatial thinking and the ways in which visualizing data in a spatial manner can allow us to make sense of massive data sets.

The Method of Ioci calls upon the power of spatial memory to aid in organizing and recollecting vast quantities of information over extended periods of time. The method of Ioci requires that a person create or call to mind any space that they know well (such as their bedroom or childhood home) and visualize the layout and distinguishing features of the space. With the setting acting as a sort of background or canvas, they can then “place” pieces of information that they want to memorize in various locations in this space. When they wish to recover the information, they take a mental “journey” through this space and “pick up” the pieces of information they’ve stored.

While this process may sound like sci-fi or a myth, in reality it has yielded incredible results. Individuals of average intelligence have used the method of Ioci to perform amazing feats of memory, such as reciting digits of pie into the thousands or memorizing sequences in memory competitions.

The effectiveness of the technique lies in the fact that the spatial and visual parts of our brain are able to form a powerful partnership. The visual part of our brain allows us to understand and remember what things “are” and spatial orientation allows us to assign context to information, thus linking that information with memories relating to that context.  For example, a person can remember a path they took through a city they visited years ago yet often has difficulty recalling a set of digits that they saw written out on a piece of paper that morning.

Spatial Memory and Data

Dashboards and explorable data visualizations are effective tools that facilitate the understanding of data sets because they allow people to physically manipulate their data with their own hands. This engages the spatial parts of our brains, and in doing so allows a deeper understanding of the information behind the numbers. This is because the manual and mobile elements allow us to rearrange the the information and thus re-orient it against many different contexts.

Mapping visualizations have also become extremely popular forms of data visualizations. The ability of marrying maps with data and geography with numbers is extremely effective because it allows us to see data representations distributed across a space on a map that we are familiar with. The element of the known space (a map of the United States, for example) combined with the somewhat ambiguous element of unknown information (such as the distribution of sales across each state) allows us to contextualize it by tethering it to a spatial area that we already have committed to memory.

In this sense, dashboards are truly worth their weight in gold to company decision makers. Executives make many decisions and judgment calls throughout the day, and it’s essential that they’re able to envision a holistic view of their company’s operations in their mind’s eye. A decision is much more well-informed if the executor can think in terms of images, maps, distributions, etc. as opposed to the blind stab in the dark made as a result of a fuzzy memory a one-dimensional excel spreadsheet.

Although we don’t still wear tunics or recite rhetoric as a sport, we still can thank the Greeks for the discoveries into the nature of human understanding that we’re able to apply to tackle modern day challenges. Because of them, we know that quantities are better remembered as sizes or masses than as digits or numbers, and data characteristics are better remembered as shapes or pictures than as labels or text. And we know that partnering visual representations of information with a spatial context allows us to not only comprehend “big data” but also neatly compartmentalize it in our minds for easy recollection.

 

Olive Kisses,

Captain Dash

 

 

The Dark Side of Data Visualization

163413_479288597199_8388607_n.jpg

With great power always comes the possibility of misuse- in the world of superheroes, that possibility commonly takes the form of an evil alter-ego. Most great heroes are well aware of this - Batman was plagued by his villainous twin Owlman, Wonderwoman battled her nefarious sister on numerous occasions, and even Spock was reminded of the darkness within him by Mirror Spock. It comes as little surprise that one of our own, Captain Dash’s right hand man Dr. Data Viz, is no exception to the alter-ego rule.

While at its best data visualization can be beautiful, illuminating and provoking, its dark side thrives off of frustration, confusion, and disappointment.

So, you may wonder, how does data visualization become one of the bad guys? Most commonly, visualization attempts go sour when you succumb to the seduction of unrealistically high expectations. You want your visualization to be beautiful, compelling, and groundbreaking. But perhaps your data results are not as impressive as you’d hoped. You may find yourself tempted to overstate your numbers in order to boost your company’s image by making the angle on the ROI graph just a little bit steeper. Or you may have a specific idea of what you want your visualization to look like, but unfortunately your data just isn’t representative of that design.

If you begin your visualization with inflexible ideas about how you want your final product to look, you will surely encounter frustration and roadblocks. Data visualization is a non-fiction genre of art, a representation of truth, and your entire company loses its integrity when you deceive your viewers by purposefully distorting your data.

It is only when we shine a light on darkness and come to understand it that we can truly defeat it. Knowledge is power, and the key to defeating our dark prince of data visualization is by knowing wherein lie his weaknesses. Realistic expectations, flexibility, honesty, and creativity are the only blades sharp enough to penetrate his cold steely armor and ultimately precipitate his demise.

Forever at Your Data-sposal,

Captain Dash and Dr. Data Viz

How to Add a Secondary Axis

They say it takes two to make a thing go right. Cheesy 80's songs aside, adding a second axis to your DataViz graph can help you view a graph from a different perspective. When done right, adding a second axis to the same chart area allows for a more colourful, richer, and compressed visualization. On top of adding another axis, you can also apply a different type of graph to make your visualization really stand out. Of course, we provide you with easy-on-the-eye colours so you can pick which ones are most suitable. Okay, let's begin. First, go to Explorer, and click the '+' button to add a source. In this example, we have chosen the number of visits to Captain Dash's homepage. The second we chose was the number of people talking about us on Facebook:

So from the screenshot above, you see the brown bars are the number of people talking about us, and the gold is for site visits. Next, click on either source, we chose 'site visits.' When the new tab opens up, you will see on the bottom right 'Left axis.' By tapping the L, it changes to right, thus giving you a secondary axis. Choose which one you would like as well as adding a different visualization:

As simple as that, you have added a secondary axis as well as a cool line graph:

Let us know via Twitter (@captain_dash), Facebook or G+ if you'd like further analysis on issues related to our app!

Cheers,

The Captain.

DataVis Showcase: Some great examples of Data Visualization Projects

If you have been following our social media activity you may notice how we often accredit those who develop impressive DataVis projects. These projects are being uploaded on a regular basis these days, so in this blog post we decided we'd pick some great projects we found compelling. They are interactive, fun, insightful, and beautiful, as most would consider well constructed DataVis projects. In no particular order, here are some we've chosen.

First Names for Males in France between 1950-2010 (Dataaddict.fr)

An innovative way of seeing popularity in boy's names in France. An interactive graph by which you can add multiple names to from an expansive list of French names, really interesting to see the changes in popularity. Check it out here.

San Francisco Visualized through Instagram Photos (Phototrails via Guardian Data)

Presented in an unintentional 'kidney bean' shape, this is a truly amazing radial plot visualization of San Francisco. Zoom right in to view individual Instagram photos around the Californian city. According to the Guardian, "closeness to the centre relates to brightness and the angle relates to hue, showing us the colours and the shades of photos that San Franciscan Instagram users want to share." Link is here.

Living Cities: Various cities mapped visually (CartoDB, HereMaps)

View and explore various cities with timelapses and traffic flowing through the city. Bite-size widgets appear to give the user a brief summary of things to do and see around each city, such as shopping, restaurants, and transport. Very well presented and good interactivity, available here.

Clear Congress Project: A Data Visualization/Mashup of Congress (by Thomas Gibes)

A number of data sources were used when developing this interesting project about the United States Congress, namely Sunlight Labs' Real Time Congress API, GovTrack.us, Google News, and Twitter. Given the increase in availability of Open Data from Governments, this was an insightful and creative idea, showing how data visualizations can play an important part in addressing governmental and institutional transparency. Check it out here.

Madrid Noise Level (20 Minutos)

Spanish city life is known to be quite noisy, and the Capital is no exception. Spanish news site 20 minutos published a cool,collective map of the city indicating the loudest neighbourhoods (in Spanish). At least next time you are in Madrid you know where to get some peace and quiet! Try it out for yourself here.

These were some that we found recently online, we hope you enjoyed them. If you have any others that you have found please feel free to get in contact: @captain_dash.

Cheers,

The Captain.

Data Visualization: an Art or Science?

Many opinions differ on the topic of how people consume Data Visualization. Is it a step back in time, i.e. is it of historical benefit? Or is it just like you would visit a gallery: you think pensively at the presentation trying different ways to interpret it's true meaning. We'd like to get deeper into the true meaning of Data Visualizations; getting past text and figures, and finding other characteristics in the data. In order to do this it's important we approach them with a pinch of salt, that is to say, to try and connect the data presented to us to the subconscious in such a way that it will yield a different understanding. Many of the projects vary enormously in subjects, formats, and so on, however there are also big differences between private and public data visualizations. Most of us only really know about the public ones, with which most of the time the data is open-sourced and more viewer reasoning. On the private side, they appear to be more functional, and perhaps more focused, as the viewing numbers are much lower.

Data Visualizations serve as multi-functional points of reference, as well as having cognitive effects on the user, triggering emotions and developing differing opinions. As well as this, people who publish their work based on data readily available to them put the time and effort into making them; in an attractive and informative manner. So gathering the data is the scientific part, but the end product is certainly artistic and can be quite easy on the eye.

This video was taken from the PBS Off Book Webisode:

The Art of Data Visualization

"It's not about "know your audience", it's "respect your audience" and really know your content" -Edward Tufte

This video goes more in detail in the creation, architecture, and variation in different Data Visualization projects. It includes, along with Edward Tufte, Julie Steele (O’Reilly Media), Josh Smith (Hyperakt), Jer Thorpe (Office for Creative Research). It is interesting to hear different opinions on Data Visualization, such as Jer stating that “Data Visualization is about Revelation – seeing something you have never seen before." What he means here is that finding a key characteristic that differentiates data science from business intelligence. Going from informative visualizations to infographics, we can see how data has emerged as a vital part of modern life that entering into the realm of art, where data-driven visual experiences challenge viewers to find personal meaning.

Faithfully yours,

The Captain

The Captain's Picks: "Beautiful Visualization: Looking at Data Through the Eyes of Experts" Aaron Koblin

To finish off the Captain's Picks mini-series, we chose a more recent title that has been a point of reference for many DataViz enthusiasts. Aaron Koblin, along with a number of creative and inspirational contributors, published a brilliant book entitled: "Beautiful Visualization: Looking at Data Through the Eyes of Experts." Just so we are clear, this book is not a 'how-to' book, rather, it tells the reader how some very well-known visualizations were made, in detail. The book consists of 20 chapters, written in an essay-style format, by 24 contributors. Some very well known Data Visualization enthusiasts are among the contributors, which makes it all the more inspirational. Taking one of these authors as an example, Noah Iliinksky,  who works as a Visualization Expert at IBM's Center for Advanced Visualization, describes beautiful data visualization as "novel, informative, efficient, and aesthetic." In order to do this, he describes it in four key steps:

1) Stepping outside default parameters: "In most situations, well-defined formats have well-defined rational conventions of use: line graphs for continuous data, bar graphs for discrete data, pie graphs for when you are more interested in a pretty picture than conveying knowledge." In other words, in order for the visualization to appear beautiful, it must be novel and create shock and awe.

2) Make it informative Noah points out the obvious here, in that there should be a clear understanding of the message and needs of the audience are key in doing so. Sometimes when creating beautiful visualizations, even the simplest of guidelines can be overlooked, such as this one.

3) Efficiency "Every bit of visual context will make it take longer to find any particular element of the visualization." In other words, visualize what matters most and eradicate the part that doesn't, or relocate it to the background so it doesn't distract.

4) Leverage Aesthetics Use simple components of graph (titles, axes, etc.) to increase utility of the visualization.

Other noteworthy authors include: Jessica Hagy, Johnathan Feinberg (Wordle), Martin Wattenberg & Fernanda Viegas (Visualizing Wikipedia). Of course the author Aaron Koblin deserves special mention, for his impressive work on flight patterns across the US along with his colleague Valdean Klump. See more on this project from his awesome TED Talk from 2011. The book does not serve the purpose of just learning about visualization tools, on the contrary, the reader will learn about data, what questions to and not to ask, and how to convey the appropriate message.

The book is available from Amazon here.

And this concludes our Captain's Picks series, we hope you enjoyed reading about the books that have been an inspiration to us over the years!

Cheers,

The Captain.

The Captain's Picks: Edward Tufte's 'Envisioning Information' (1990)

For those of you who have followed the Captain Dash story since the beginning, you will know that we always give credit to mentors and people who influence us in offering better Analytics solutions to our customers. In this blog post, we are going to give you, our followers, a brief review of one book that has had a big influence on us over the years.

Nowadays, given the massive shift to devices and technological revolution, we hear less and less about how people use books as points of reference. Here at Captain Dash HQ, we have an abundance of devices, however, there are still some books lying around for our Captains to try and get some inspiration. One book in particular lying around is Edward Tufte's 'Envisioning Information.' This book covers a wide range of topics, and puts statistical graphics into a wider context of design. The book splits into 6 sections:

1) Escaping Flatland - an introduction into the problem of displaying three (or more) dimensions on a two-dimensional surface;

2) Micro/Macro Readings - the tension between providing both a general overview and specific details;

3) Layering and Separation-the visual stratification of various aspects of data;

4) Small Multiples - the use of repeated images to show options or sequences;

5) Color and Information - the effect of color on design;

6) Narratives of Space and Time - the problems in portraying time, the fourth dimension.

Considering how important design has been for us, the way this book is well laid out and concise. It reads well and clear, which is what Tufte advocates throughout. He opines his own views as universal truths rather than just his own two cents. Most of all, we like Tufte's enthusiasm throughout this book. He is unbiased when giving examples, good or bad, which makes it easier to critique. From the bad design analyses, we could figure out what worked for us or not, and gave us less time spent going back to the drawing board.

We highly recommend this book if you take a keen interest in design and look to find more resources than just online, it's always good to come across a blast from the past! The book is available to purchase here on Amazon.

Cheers,

The Captain.

 

 

It's Monday, and nearly Summer. More Importantly, Data Visualization is Growing...

We all don't like Mondays. You're after a jam-packed weekend, and you're tired. But here at Captain Dash we're full of life. Why? It's nearly Summer. Also, there are plenty of developments in Big Data that we are looking forward to. Here's why. As you already know, Big Data has become the buzzword of 2013. More and more people are investing in it and this year will see an explosion of new companies entering the industry.

According to Scott Gnau, President at TeraData labs, “the future of business belongs to those enterprises that embrace the big data analytics movement and use it to their advantage." If the sentiments of Mr. Gnau are anything to go by, this year could see a whole different approach into how people consume and manage their data.

'But Captain, what about Visualization? This must be a facet of the Big Data Revolution that companies will also embrace?' Of course, visualization is of equal importance. Besides all the pretty graphs and interface, it is worth noting that the main aspect of data visualization tends to get lost when just focusing on it's looks, rather than accurately representing data in a form most easily consumable by the viewer. Public Health & Development blogger Brett Keller gives an honest critique of what data visualizations should be more focused on, rather than just the color schemes. In referral to an infographic about mortality rates, he thinks that "raw numbers of deaths tell us very much, and can actually be quite misleading."

Are Dashboards and Data Visualizations going through a similar transition as Powerpoint did in the 90s? Ray Cha of futureofthebook.org articulates that there were a number of "factors required to transfer text into a digital medium." Furthermore, he believes that time wasted in the process of making presentations was "at the expense of thinking about and developing content." We certainly don't want to compare them both too much. Make use of your visualizations for what they are about, not how they look.

Democratization of Data Visualization

All for one and one for all! Does that motto work with the concept of data visualization? It should, if we're talking about the democratization of data visualization. Might be a mouthful, but it's an important subject in today's world brimming with dataviz solutions for marketers who want to see their important info in a visual way. Do they want someone else doing it for them? Or should they have the power in the palm of their hand?

There are many solutions out in the digital marketing world for managing analytics, business intelligence, big data, and data visualization. Captain Dash is one solution, Tableau, Datahero, are others, and there are many more ways that marketers can see their data. The differences between some of these solutions is the control and power allowed to the user. Some other firms have complete control over the visualizations they make for their clients, and create them based on client demand and specifications. This seems to frequently cause unnecessary miscommunications- client tells the firm they want this that and the other thing, the firm presents them with a visualization that shows that that and this thing. The client is unhappy, the firm didn't get it right, and a whole mess of back-and-forth ensues.

So why not give the client the power to control, add to, delete from, and change the look of their own visualizations?

Bill Franks wrote in this Harvard Business review article :

"While many users of the new visualization tools spend most of their time generating basic output, they get really excited about their new-found freedom to navigate the data and view it from any angle desired. While the graphics generated may be simple, users are much more confident that they contain the right content. The implication is that many organizations may not be getting the full benefit of their big data and visualization investments."

So it seems that the best way to get the most out of data visualization for these organizations, while retaining their ability to "see their data from any angle," is to invest in a solution that allows them control over what they create. If a user can create on-demand graphs of whatever metric they choose, reaction time for marketers can be that much quicker. If a user can create a visualization in the time it takes to send a request to their viz vendor, then the world will spin that much faster for that user. And in the end, isn't that the main goal? To make the world a smarter and faster place?

Put the capabilities in the people's hands, and watch insight grow.

Faithfully yours,

Captain Dash

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Which Social Media Superhero are you?

As we know, social media has become a key component in any marketing strategy. Not only is it a quick, efficient, and oftentimes cheap way to reach customers on a much more personal basis, but it is also an opportunity to respond to customer data gleaned from social media with more targeted campaigns. What's more, businesses can respond to their customers complaints, demands, and praise in real-time with a well-worded 140-character message.

So, unsurprisingly, social media superheroes have emerged. These are seemingly normal internet users, but put them in front of a social media platform, and their true identities emerge.

Click for the full-size infographic. 

Which superhero are you? Feel free to leave a comment or shoot us a Tweet!

Thanks to uberVU blog for this über-cool infographic.

Your favorite data superhero,

Captain Dash