Earlier this week the British government approved plans for the first domestic high speed rail network, scheduled to be in place by 2026. For some this upgrade was long overdue and certainly Britain appears to be lagging behind it’s European counterparts, handily from Bime HQ in Montpellier in the south of France we are able to get the high speed train up to Paris in just over 3 hours (597km).

The announcement gave us the opportunity to compare some high speed rail networks worldwide. Using Bime we were able to take some general statistics from the Guardian Data Blog on the distance of current and planned high speed rail lines and add some basic population and land area information to create some visualizations comparing high speed rail networks in different countries.

As always, in Bime dashboards are interactive for viewers, click the link or the image to view and play around with the data.

View the dashboard here

Put your visualizations in a logical order

The visualizations which show the key metrics should be at the top and to the left of the dashboard as this is where research shows the user will direct most of their attention (as shown). Make sure that related visualizations, or visualizations where a comparison can be made are placed next to each other. The dashboard should be arranged to make the end user consume the dashboard in the order the dashboard creator intended it to be consumed. In Bime changing the layout of visualizations on your dashboard could not be easier, once in the edit mode simply drag-and-drop.






1. Be space efficient







Try to minimize the amount of ‘unused’ space on the dashboard. Bime makes this easy to do with some simple built in customizable features. Why not try these few simple tweaks to optimize space on a dashboard.

• Delete unnecessary legends
• Put labels inside of the visualization itself rather than below or by the side
• Rotate your labels to fit more labels into a smaller area
• When using an ‘explosion’ measure use the cover view instead of the tile view


















2. One screen?

Ideally a dashboard would always fit one screen without the need for scrolling, switching between pages etc. to allow the user to dig into the data, quickly and easily. However, this doesn’t mean visualizations should be crammed onto one page at all costs. If a dashboard doesn’t fit one page, the next best thing is to organize the dashboard so the viewer has only one scrolling bar, either to scroll down or to scroll across, but preferably not both. Alternatively in Bime several dashboards can be linked together to be listed under different tabs but under the same heading. This is usually only advisable if there are natural divisions in your data.

3. Size your visualizations adequatly

If possible, make your visualizations big enough so that all information on the visualization can be viewed without having to make further clicks on specific points to find out the underlying data. If the space you have allocated for a visualization isnt enough then that visualization will require its own scrolling bar, this makes it more difficult for the user to get the information quickly – ideally, visualizations should be made large enough so they don’t require their own scrolling bars. However, making your visualizations too large can often result in making the overall dashboard inconveniently large, therefore a trade off may be required.

Remember, it is important to have the end user in mind, how will they be consuming the dashboard? For example if the end user will be viewing the dashboard on the Bime mobile app then it may be a good idea to consider making the visualizations larger.

4. Align the elements of your dashboard

In all forms of web design, designers often use a grid system, leaving small gaps between elements on the page to ensure the lines on the page align where possible (see the example below from The Guardian homepage). In Bime users have the option to utilise the free flow grid layout setting or let Bime automatically align size and position of visualizations on a dashboard.



5. Utilize color

Color can be used to show patterns, set the overall mood or just make the dashboard look sleeker and the user has several different options of how to use color on the dashboard. Using different colors to the rest of the dashboard can draw attention to certain parts and using similar colors can also tie two parts of a dashboard together. Generally, a complimentary color scheme can drastically improve the appeal of your dashboard as a coherent color scheme draws the whole dashboard together and makes it look more professional. A good starting point is to identify colors which are prominent in any images or visualizations you have used on your dashboard and then use a color scheme to compliment these colors. However, the color scheme of your dashboard can also be used to provoke certain emotions or use colors which are related to the information you are trying to show on the dashboard. Different colors can be used as running themes throughout a dashboard to represent different groups, such as with this football dashboard from our showcase in which throughout, red represents the English league and blue the French.



Certain color combinations will be more pleasing on the eye, the color wheels below are taken from a Kissmetric blog post on the subject.



6. Keep your dashboard updated

In Bime, if selected, the built in cache, Deja Vu, will take a snapshot of your data therefore if your original data source is on premise the user is still able to share the dashboard created from this data, online. The deja-vu is updated automatically every time the dashboard is loaded and saved and can be scheduled to update automatically at regular periods, for example daily. In Bime all the data on the dashboard can easily be re-loaded from the query cache, from the data cache and from the data source. It is also possible to allow users to update the cache to allow them to view a perfectly up-to-date version of the dashboard.

7. Make sure you provide context to your data

In Bime the stunning range of visualizations bring the data to life and as they say ‘a picture (or interactive visualization!) is worth a thousand words’. However, again it is important to think about the end user, what information do they need to consume the dashboard? Make sure the dashboard includes adequate labels, legends and provide enough data on the dashboard to allow the user to get the information they need.

8. Allow interactivity on your dashboard

Which interactivity features may be useful for the end-user to get the most out of the data? The user may want to look at slightly different metrics to the owner of the dashboard or look at the underlying data behind a visualization on the dashboard. In Bime dashboards are interactive and everyone viewing the dashboard can click on a specific data point to view the numbers associated with that point. Additionally, in the premium version of Bime, the owner of the dashboard can choose to allow external viewers the ability to drill through, drill down and decompose the data.

9. Use text efficiently

Make sure that the text you have used on your dashboard, such as visualization headings, helps to explain the dashboard, graph titles are important and should signal exactly what that visualization shows. Use text to direct and assist the user in certain parts of the dashboard using rich text including font size, type and hyperlinks.

10. Avoid overloading the user

One of the main purposes of a dashboard is to provide a clear summary of the data, quickly and clearly. Therefore be selective with visualizations and only provide information which is needed for analysis. If it is essential to include extremely detailed visualizations in the dashboard then it can sometimes be useful to add them nearer the bottom and put the visualizations which provide a more general overview at the top so as the user works there way through the dashboard, layers of detail are gradually revealed. Alternatively in the example just mentioned, if they just want to look at the dashboard quickly then the key metrics are summarized as soon as they click to open the dashboard at the top of the page.

This is obviously only an express guide to dashboard design. What killer tips do you have for designing stunning dashboards? To view our selection of showcase dashboards, click here

BIME is a dashboarding and data visualization tool that helps you shine new light on your data. Click here to go to our Pricing & Plans page and sign up to turn your data into dollars!

Did you know? The Doctor has fought more than 300 villains and monsters in his time. Find out who they are – and which appeared most, as well as when they first hit the screens. However, the data doesn’t include villains exclusively in Doctor Who books, audio books and spin-off shows – only the televised serials and only enemies (as opposed to protagonists).

The infamous Dalek has appeared more times than any other Doctor Who villain.

This particular data was sourced from: The Guardian Data Blog.

Data Format: (Online) – Google Spreadsheet.

Click on the image below to access the dashboard.

The images below are only snapshots, Bime dashboards are interactive and underlying data can often be examined so to access the fully interactive dashboards click any of the images or click here.

From the dashboard, a number of conclusions can be drawn. Firstly from the treemap it is clear that scoring in the tournament has historically been dominated by the big three Southern Hemisphere teams of New Zealand, Australia and South Africa. The treemap is perfect for showing two measures at once, so whilst the size of the sections on the visualization represents the average points scored, the colour shows the number of yellow cards. The more blue the section, the more yellow cards received, therefore it is clear that whilst the top 3 nations have been relatively well behaved, Tonga have picked up the most yellow cards.

It is often touted that the key to success is keeping your discipline. Whilst the chart shows that this is the case in 2011 with the eventual winners, New Zealand, who have a very high points scored total and relatively low penalty count, this is surprisingly not the case with the runners-up in the tournament France, who have an extremely high penalty count. Bime allows the user to display two measures with two quantitative scales on one chart therefore a relative comparison can be made, as shown with the points and discipline chart below.

The stacked bar chart [below] again shows total points scored by each nation in the 2011 tournament however the stacked approach allows us to view break down of how these points were scored. The chart is sorted by the points scored via tries so a few nations literally and figuratively stick out of the chart; Scotland, Tonga and France all scored lots of points but a comparatively small percentage via tries. In Bime it is easy to highlight a section of your data, for example if we just wanted to look at points scored by penalties we could do so by hovering the cursor over ‘penalty points’ in the legend [as shown].

From the last visualization we can get a general overview of the success of each nation through history based on the number of points they have scored in each tournament (although as we saw in the previous visualization, scoring points doesn’t necessarily lead to success!). Bime allows us to click through the different nations manually or by clicking the ‘play’ button, view them automatically one after the next. Looking generally at the statistics it appears that less points overall have been scored at the two most recent world cups, with the 1999 and 2003 being more fruitful affairs with regards to scoring. This is especially the case with England [displayed below], their highest point hauls coming in 1999 when they reached the Quarter Finals and in 2003 when they were crowned champions.

With the help of Bime you can transform virtually any data into stunning intuitive visualizations and dashboards. To view our gallery of showcase dashboards click here.

Get started with Bime now, sign up for a free 10 day free trial here.

In this months newsletter:
• Bime recognized in Gartner Who’s Who report
• Client Testimonial: Spicy Lemon, Dutch anti-virus software distributor
• Client Testimonial: Bugseye, Australian business consultancy
• Dashboard of the Month: Analyze your email campaign

Read it here!

The diagram above positions the vendors into 3 categories:
1. Dashboard Tool Vendors=> vendors of dashboard solutions (rather than pre-packaged)
2. Business Intelligence Platform Vendors => contains the ‘traditional’ vendors
3. Analytic Visualization Tool Vendors=> vendors oriented towards analytical data visualization

Bime is positioned at the crossover of two categories: Analytic Visualization Tool Vendors and Dashboard Tool Vendors. Obviously, we would like Bime to be positioned at the centre of the 3 categories but only Microstrategy and QlikTech are currently positioned here.

An important point to note in this study is that the “pure cloud” actors and the “installed” traditional type of vendors were treated the same way and Bime ranks in two of the categories. The traditional vendors mainly occupy the category “BI Platform”.

The introduction to this study specifies how data visualization gives new life to BI tools and how to the delight of analysts, interactive dashboards are replacing static dashboards, allowing for ad hoc analysis for the user. The analysis also focuses on the growing number of small and new vendors offering highly advanced analytical capabilities often built primarily for business users as oppose to more technical IT users.

The report is available for purchase here, in which a summary of Bime and other solutions is provided.

Data sourced from: Mashable 2011

Diving into the data
It was interesting to see that there are still some iPhone owners that have the very first generation iPhone that came out in 2007 – against almost half of the surveyed who hold 2010′s 4th generation handset.

Text messaging proved to be the activity which iPhone owners dedicated the most time to above all other activities (19% of device usage time was attributed to SMS activity) – followed closely by calling (17%), emailing, apps and Internet (all 16%).

The next metric we looked at was daily iPhone usage – how many times the owner uses his or her phone during a given day. If you’re a smartphone user yourself, the results are probably relatively unsurprising – more than 80% of owners surveyed said they used their iPhone more than 15 times a day. The numbers peaked with 33% of respondents citing that they use their iPhone between 30 and 49 times a day. If you use your iPhone, say, 40 times a day, that’s once every 36 minutes!

Next up was jailbreaking information – what percentage of phones had been jailbroken vs. the percentage of those that hadn’t. Just over 1 in 10 owners reported jailbreaking their iPhone – 11.7% of total respondents to be exact.

The data also touched on some of the changes that iPhone owners wanted to see in the upcoming iPhone 5, where longer battery life, no long-term contracts and unlimited data took the top spots. Other interesting, but less coveted ones, included unlimited storage in iCloud, full HD video and 3D display. Near the bottom of the preference list was a feature Apple is renown for, and one which has been the subject of wide speculation: style and design – proving that the 5th generation’s predecessors have been so far satisfactory in this area. It perhaps should also perhaps be acknowledged that some of these wishes such as the length of contract are not totally decided by Apple and would be down to the network providers.

Apps are a huge part of the reason for owning an iPhone, and the distribution of free and paid apps was reflected in the data. Paid apps generally seem to dominate where an owner has 10 applications or less, and then free apps take over where the number of installed apps rises above 11.

Lastly, the sample was U.S. based, so the network distribution data was restricted to American carriers. AT&T was the sole carrier of the iPhone in the U.S. until February 2011, and so understandably claims three-quarters of the market share. The stats show that Verizon has a respectable 19.5% share of the iPhone market, whereas other carriers combined make up the last 5%.

Access the dashboard by clicking the image below

Do you have an iPhone? What improvements would you like to see in the iPhone 5? Hit the comments.

In our newsletter this month:

• » We Are Cloud Launches Bime V3.0 at DEMO Fall 2011
• » Watch Bime V3.0 in action
• » Bime V3.0 support documents
• » Dashboard of the Month: DEMO Conference Stats

Read it here!

To give you an idea of what you could achieve in a few minutes with Bime, we built a basic dashboard containing (dummy) Adwords campaign metrics data. Imagine the possibilities if you spent a couple of hours on it!

You can access the dashboard by clicking the screenshot below.

Tweet this dashboard! Tweet

Don’t forget to check out some of the other sample dashboards we have built in the Bime showcase.

The graphics below are only images, if you open the dashboard in the web player in your browser these visualizations are interactive and using the row selector tool, more information can often be examined. To access the interactive dashboard click here. The only measure shown from the original data-set was the fee amount. The remaining averages, calculations and queries have been executed within Bime. In Bime you can easily distinguish between the attributes by assigning a color, thus, throughout our dashboard red=English Premier League and blue=French Ligue 1. Throughout the dashboard, ‘N’ refers to the number of transfers. Thanks to the concise way we were able to display the data, and by querying the wider dataset, a number of conclusions can be drawn.

The first conclusion to draw is that the Premiership is a bigger money league, something often assumed, but now clear to see. The average fee in the Premiership is €6.6m, against €3.8m in Ligue 1, and the distribution of fees is startling. In Ligue 1, only Pastore (€42m to PSG) arrived for more than €12m, while the Premiership saw 21 players move over that price. The discrepancy is even bigger if PSG and the funding from their new backers is taken out of the equation; without this, the average fee drops to €3m, and the highest fee, in or out, would have been €12m – and he (Gervinho) went to Arsenal. In Bime, queries can easily be adapted, such as with the example above (L1 clubs without PSG). This can be performed using groups, and including / excluding the attributes or measures you wish to include in the query.

In total, €198m moved within the Premiership, which had a net spend out to lower domestic leagues of €70m, and sent €149m net abroad. The most expensive market was internal, averaging €9m per player (possibly reflecting the much touted ‘English player premium’). Conversely, the majority of Ligue 1′s outside spend was domestic, with €32m net staying in France and only €14m going overseas. In Bime, using color weighting (and also if needed but not shown below, size weighting) on a range of different visualizations, we are able to show several different measures on one chart. The pie charts below, taken from the dashboard, show both where transfers were made (segment) and average transfer fee (color weighting).

Other differences in approach can be seen – players are twice as likely to move on a free in Ligue 1, with the area treemap (below) showing the clubs who did the most free transfer and loan moves. While the domestic loan markets are fairly even, with both leagues mostly sending out their younger players to lower domestic leagues to gain experience, the Premiership is nearly six times more likely to send players overseas for a spell, Arsenal picking up plane tickets for seven players, Chelsea for four, and Liverpool and Manchester City three.

The effect of PSG’s newly fattened wallet may be a cause for concern in France, as the massive cash injections at City and Chelsea were in England, but we will have to wait and see if this is the bellwether for a change in approach in Ligue 1. As things stand, Ligue 1 may be seen as a ‘junior’ league within Europe, but with UEFA’s financial fair play rules coming into view, the less bloated finances of the French league (see the bubble chart below) combined with the possibility of soon leap-frogging Italy in the rank co-efficients, may be a recipe for longer-term stability as Ligue 1 teams are able both to attract, and hold onto, important players.

With the exception of PSG French clubs tend to spend well within their means. Click the chart to view a fully interactive dashboard to see which circles belong to which clubs.

The dashboard summary of the summer transfer window highlights how Bime can take complex and large amounts of data, manipulate it and display it in an easy-to-digest way with some stylish looking visualizations. To explore how Bime can transform your data, sign up for a free trial (no credit card required!).

Access the dashboard here

Authors: Philippa Booth & Jonathan Gardiner