Category Archives: Visualization

How to gauge data through charts – Creating Gauge Charts

A common question that comes up in support for XL Cubed is how to add charts that look like a dial, or a gauge. Something like the below:








These are actually very easy to make and publish to the web, plus they have the further bonus of adding something different to make your reports look more professional.

Once you have your data ready, add a new doughnut chart and configure it to show the information you want it to.











This will give you a simple doughnut chart.











Next up, pick the cell that contains the information you want to show in the middle of the doughnut chart and reference it in another cell. For example, in the below example we have the two numbers that make up our doughnut chart in cells B3 and B4. Cell E3 contains the information we want to show in the middle of the doughnut chart.






As you can see, the formatting is different in E3 to the other cells. This is because we have formatted the cell to show the data how we want it to appear in the chart.

Once we are at this stage, it is just a case of transferring the number to the middle of the doughnut chart. You can do this by selecting the formatted cell, in our case E3, copying it and then paste special as a ‘Linked Picture’ anywhere in the worksheet (we will move it into the chart in the next step).
















The ‘Linked Picture’ appears as a cell but it actually acts like a picture so, lastly, move the picture into the middle of the doughnut chart so it looks how you want it, then, right click on the new picture and select ‘Send to Back’

















As the cell is a ‘Linked Picture’ Any changes you make to the cell you copied, formatting or data, will update the image.





Your Gauge Chart is complete! These charts also look good when published to the web.


Report Flexibility, with Control

Sometimes we want to let report users modify the structure of a report but to govern exactly what they can and can’t do. While Grids can be restricted at a granular level to enable and disable functionality, that approach still requires some degree of product knowledge by the user.

XLCubed provides the XL3SetProperty() formula, which enables manipulation of many of the core objects such as Grids, Slicers and Small Multiples. It means report users can have simple slicer selections to change the structure of a report, what’s being displayed in a chart, or to vary the chart type. It gives flexibility within the report, but requires no product knowledge from the end user which can be crucial when delivering web reports on a widespread basis.

One common example of usage is where the hierarchy to be viewed in a grid needs to change based on the measure a user selects (depending on the structure of the cube some measures may not be applicable for all hierarchies). Typically that would need to be handled in two Grids, but we can use XL3SetProperty to bring this together, and also to give user choice on the associated Small Multiple Chart view.

The final published report is shown below:




If the user selects an “Internet” measure, we show Customer Geography on rows, whereas a “Reseller” measure should show Reseller Type on rows. The same logic applies to the Small Multiple chart. In the screenshot below, the user has selected Reseller Gross Profit as the measure, and ‘Stacked Column’ as the chart type. You can see that the hierarchy on rows has been switched, as has the split within the individual charts, allowing the user to easily vary their view of the data with simple button selectors.




This is implemented through the following key points:

  • A lookup table in Excel to determine what hierarchy is applicable for each measure
  • An Excel list showing the available chart types – this is used in the Chart Type slicer
    • The chart slicer outputs its selection into cell $AG$10
  • The measure slicer is linked directly to the grid and the small multiple, but also outputs its selection to an Excel cell ($A$B4)
  • A vlookup determines which hierarchy to use based on the selected measure
  • Three XL3SetProperty() formulae now control what is displayed based on user selections:
    • $AB$7 – sets the grid rows
    • $AB$8 – sets the small multiple columns
    • $AB$7 – sets the chart type




The approach gives a deep level of access to the key XLCubed reporting objects, and enables controlled flexibility within web and mobile-delivered reports. No programming is needed, just a mid-level understanding of Excel itself, and XLCubed.

This is just one example of what the approach can achieve – it’s really limited only by imagination. See XL3SetProperty() for more detail, or contact us if you’d like the example workbook.

Click & Submit!

We’ve had a few queries recently where customers want to provide web reports with a number of slicer choices, and to have the report refresh just once when all selections are made, rather than the default refresh after each selection. It can be achieved in a couple of ways in XLCubed, read on for more…

The key to this approach work is the ‘Wait for Submit on Web’ option on the slicer properties, shown below on the Behaviour tab of the slicer designer:


This means when the slicer is changed it does not refresh the report straight away, and if you set this on multiple slicers users can then press the ‘submit changes’ button on the toolbar shown below after they’ve made their selections.



Alternatively, and to make it more obvious for web users you can have them click on some text or an image in the report itself to call the refresh, as in the examples below.

I’ve created a simple report below with five different slicers.  Note the “Refresh“ to the right, created using XL3Link().



The XL3Link statement is available from the Insert Formula menu on the XLCubed ribbon:




It’s most often used to move the focus to another area of the report while passing parameters to enabled linked-analysis in a multi-sheet report. However, here we can use it to call a refresh.

We can leave the “Link to” parameter blank, and also the Target and Value cells. The last parameter, LinkType calls SubmitChanges on the web, so the syntax will look like below (you will need to update the XL3Link statement to include this parameter):


There is more guidance on the general use of XL3Link on our Wiki at:

So when we publish our report to our web server we can change the slicer choices as required but it’s only when we click the Refresh button that the report is refreshed.



If we’d prefer to display an image for the user to click on rather than text we can use XL3PictureLink in a similar way.  When using XL3PictureLink we can display any picture – we’ve used a generic refresh icon but it could easily be a more corporate-applicable image:


XL3PictureLInk is also available from the Insert Formula menu on the XLCubed ribbon:


Browse in the window above to locate the Picture file to insert and remember to check the Perform a Submit Changes on Web box.

There is more guidance on XL3PictureLink on our Wiki at:

This is the published report using XL3PictureLink, the user makes the required selections and clicks refresh.sub8


So it’s as easy as that – two ways to ensure that your users can change multiple slicers on web-published reports before calling the refresh, and without you having to direct them to the standard submit changes on web button.

Bump Charts in XLCubed

So today’s blog is about adding Bump Charts in Excel using v8 XLCubed.

Initially a Bump Chart looks the same as a line chart – the difference is they plot the rank position rather than the actual value.

Let’s imagine that I sell a product in a marketplace with 10 other competitors. I may like to see how the rank position of my product and the competition changes over time to check if I’m gaining or losing market position. It’s a common scenario in pharma, where we have a good customer base.

You will usually want dates on the category axis so the trends are shown across time. The series then holds the items to be compared, in this case the products.








Our example has been set up with Measures on Headers, Product Categories on Series and Date Calendar on Categories.  For more information on using Small Multiples in XLCubed please visit Small Multiple Charts.

The currently selected measure is Reseller Order Quantities (selected though the Measures slicer)






for the eleven months prior to April 2008 (selected through the Date slicer)






for a subset of products.

Looking at the bump chart you can see that I’ve selected Road Bikes and Mountain Bikes for easy comparison.  You can quickly see that the rank position for Road Bikes dropped quite dramatically from May 2007, picked up again in September before dropping again in November and rising in December through to February 2008.  The change for Mountain Bikes, on the other hand, was less dramatic, rising and falling slightly, steadying in February 2008 before dropping again the following month.

To create a bump chart just select Line – Bump as the Chart Type on your Small Multiple chart. The neat part is that all the rankings are worked out for you behind the scenes, without the need for lots of complex Excel gymnastics trying to work through the full result set month by month.

Excel heat maps made easy!

With the recent release of version 8 we’re going to blog about a number of the new features, starting with how to create a heat map in Excel.

Here’s a fairly large table showing sales for thirty six products across twenty six US states:


There’s a lot of data here but it’s not giving us any helpful information as the table is too large to see any pattern or comparison.

A heat map could be a useful way to give a quick visual picture of the spread of the sales volume. Let’s add a simple heat map, new in version 8 of XLCubed.

Select the data area in the table, and then from the XLCubed ribbon select the InCell-Chart group, and heat map:



As we have already selected the data area to be charted this prompt is already showing the correct cell locations.

Choose the formula destination (where the formula controlling the chart will be located), and the Chart destination (where the top left cell in the chart area will be located).

We can now define the look of the heat map in the Chart Format dialog:




We have set the low and high colours to define a blue colour gradient.

Outlying values could potentially skew the chart so you have the option to exclude these by setting minimum and maximum values.  Select the icon to use, squares in our case, and the number of steps or bands to split the range of values into.

We have pre-arranged the Excel cell sizes to be squares, and this is the resulting heat map:



You can now quickly assimilate the spread of values in a glance, and note the higher sales volumes in Maine, Michigan and Missouri for Road, Touring and Mountain Bikes.

To alter the formatting of the chart simply double click on any one of the squares in the heat map, or on the chart formula to bring up the formatting dialog.

If you are not already a user of XLCubed you can get started with an evaluation of XLCubed by going to our registration page.

Excel BI myths debunked – #6: No report sharing & distribution

Here we continue our theme on the myths which get propagated about Excel based BI. The next argument is that Excel BI cannot handle widespread report sharing and distribution. Base case we actually agree with this one, and that’s why we invested in developing XLCubed Web Edition specifically to address it.

Understandably, sharing an Excel workbook around hundreds or thousands of users is not something which many companies will consider. A web based distribution approach is much lighter and easier to manage. The drawback is that most web based report design environments lack the flexibility and latent user skill base of Excel. XLCubed provides a simple way to push data-connected reports developed in Excel to a portal based environment, where report consumers don’t require any software installed locally, other than a browser. The reports can also be accessed interactively through our native mobile apps for Apple, Android and Windows phone 8.

XLCubed Web is self-sufficient and does not require SharePoint. For customers with SharePoint and keen to retain it as a centralised environment – no problem, XLCubed Web can integrate so tightly within SharePoint the end users won’t even know it’s there.

Excel based users can become web and mobile report designers in minutes. XLCubed uses Excel as a key part of the BI solution rather than as the entire BI solution, and it’s that which allows us to address the sharing problem, along with the other myths we have identified in this blog series.

 from any version of Excel:


…to web…


…to mobile.


Some Excel BI myths debunked: #3 – limited dashboards

#3: Limited and difficult to Maintain Dashboards

Third on our list of common criticisms of Excel focused BI, is the limitations of Excel Dashboards.

“Excel dashboards are ugly, limited, and inflexible…”

It’s possible to build a truly awful dashboard in pretty much any dashboard tool. No tool is magic, ignoring the Doctor’s Sonic Screwdriver of course, and if you make bad design choices when building a dashboard the end result can be a mess. Similarly you can build a pretty decent dashboard in most tools. So even in base Excel with no additional software you can build a dashboard which looks good, and many people do.

In native Excel there are undoubtedly some limitations around the available chart types, and the handling of dynamic charting. However you do have the benefit of very fine grain control over the layout and positioning of tables and charts. The camera object also lets you break out of the fixed column width which is sometimes seen as a limitation.

XLCubed extends the core charts available in Excel with a rich library of in-cell charts, small multiple/trellis charting, mapping and TreeMaps. It means you can deliver more in Excel visually, rather than have to leave the environment totally. Dashboards mean different things to different people, for some a dashboard can be a table with a chart, but most contain significantly more than that. The example below uses a mixture of native Excel charting and XLCubed in-cell charts.


It’s based around a sample personal finance data set, and brings a lot of information together in hopefully a visually appealing and effective way.  If you want to build a highly formatted and relatively densely populated dashboard like this, it’s going to take more than a few minutes in any tool, no matter what the marketing says. In reality you’ll most likely struggle to get the exact layout in a widget based dashboard tool as you lose some of the fine-grain control over table and chart sizing which you have in Excel.

Dashboards can be fundamentally simpler than the first example, but require more specialised chart types like the example below. In this case it’s a dashboard built in XLCubed Excel Edition and published to the Web, looking at fuel pricing for a downstream oil company (fictitious data). It’s a ranked table of data for a selected county in Florida, and is then using an extended boxplot to display the price distribution in the market, and a map to show the Revenues and Volumes geographically.


One major issue with Excel dashboards can be the maintenance. If it’s an Excel-only dashboard, bringing in the new data, and checking all the links can be a time consuming process. In an XLCubed environment the cube is updated behind the scenes and the next time you open the report you’ll get the updated data, the ongoing burden of maintenance is largely removed.

So in summary, Excel when well used, is a very good dashboard tool, and XLCubed extends the capability further still in terms of available chart types, flexibility and maintenance.

Some Excel BI myths debunked #2: Inflexible Charting

#2: Inflexible Charting

Continuing our discussion of common criticisms of Excel focused BI, let’s take a look at charting.

“Excel charts are static, inflexible and you need to start from scratch if you want to change them.“

The flipside is that everyone knows how to use them, and in reality many charts in business reporting are in effect static – the numbers being charted change, but the chart layout and number of elements being charted stays the same.

Of course there are cases when charts can vary considerably with the data, or perhaps you would like to be able to drill into more detail on the chart, or to quickly display multiple charts split by one variable. Excel charting can’t handle those scenarios, but XLCubed caters for it through Small Multiples.  The example below depicts river water quality in different regions of England. It could be built in native Excel, but would be a painful and time consuming process. With XLCubed it’s a drag and drop process in our small multiple designer.


If the number of regions being reported changes, the number of charts being plotted will automatically stay in sync, and there is a direct data connection rather than having to maintain Excel ranges etc.

Sometimes with charting small is beautiful. Perhaps we just want the key numbers with a Sparkline alongside, or a bullet graph or bar chart to display actual to target. Native Excel 2010 and 2013 can handle the Sparkline, but not the ability to then drill the report and have the Sparklines extend, and there is also the issue of needing to bring the data itself into Excel before charting it.

XLCubed Grids can contain dynamic in-cell charts which build the charts as part of the query, and as such are drillable and remove the need to maintain a data range in Excel as shown below.


So XLCubed brings the type of dynamic charting being described to Excel, and provides a simple web and mobile deployment option.



Current and Previous month reporting made easy

We’ve all been there. Our shiny new dashboard or report pack is finished and ready to go meet its users.  We’ve presented the key information clearly, we’ve followed all the data vis guidelines on effective charting and use of colour. We like it a lot, and we’ve thought ahead and built in lots of flexibility with slicers and managed drill paths so it can already help answer some of the questions it will doubtless raise.

It’s a little disappointing then that one of the first pieces of feedback is that the senior execs don’t actually want to use the interactivity much. They want to open the dashboard and see the current month picture (or previous month), and don’t want to waste valuable seconds selecting the month in a slicer…

Joking aside, in lots of situations it’s a sensible request, and there are various different ways to handle it in an XLCubed / Analysis Services world. Often this will be for a multi-sheet report incorporating grids, formulae, and charting elements and we need a centralised point to handle the month selection – enter the XL3MemberNavigate() formula.


This lets you pick a hierarchy and a level, and you can specify that you want the Last member (first and previous / next are also available). It’s available in the XLCubed Insert Formula dialog. In our case we’d pick the date hierarchy, the month level and choose Last, generating a formula as below:


The issue is that at this point it has no concept of data, it will give you the last month available in the hierarchy, not the last month with data. However that’s just another parameter away, we can add dimension member pairs to force a data check, as below, where we are checking that data exists for the “Reseller Sales Amount” measure.

=XL3MemberNavigate(1,”[Date].[Calendar]”,”[Date].[Calendar].[Month]”,”LastMember”,0,”[Measures]”,”Reseller Sales Amount”)

So that will return the last month with data, and as we know in XLCubed all grids, formulae and XLCubed charts can be based off a cell. The Xl3MemberNavigate() cell becomes the driver for all time selections in the report. Job done. Or is it? What if you actually wanted the last complete month? :

=XL3MemberNavigate(1,”[Date].[Calendar]”,”[Date].[Calendar].[Month]”,”LastMember”,2,“[Measures]”,”Reseller Sales Amount”)

Adding the addional ‘2’ parameter means it will go back an additional month, hence giving you the last completed month.

In our experience this is far and away the easiest way to handle current or Previous month reporting, and we hope you find it useful if it’s new to you. For more information on XL3MemberNavigate check our wiki.


Bandlines in XLCubed

In early January this year Stephen Few introduced the concept of Bandlines. He identified a useful extension to Sparklines, making use of shaded or coloured horizontal bands to provide more information on the context of the trend line itself. See Stephen’s article on Bandlines and the thinking behind them for a detail description.

The Sparklines are ideal for showing individual trends in a small amount of screen real estate, and we use them extensively in dashboards, typically in a ‘visual table’. By definition Sparklines are small, and to make the trend easily readable, they are typically scaled individually so that each Sparkline uses the whole vertical axis. This means they do not give any impression of the scale of the numbers involved across different rows. It’s possible to use a common scale, and while sometimes that works more often it means many of the rows with smaller values are excessively flattened.

Bandlines address this by introducing horizontal shaded areas depicting the lower, middle and upper quartiles and the median represented by a line. The user can determine the context of the bands. The two most common examples would be plotting recent trend in the context of a longer period, or plotting individual rows in the context of the overall set of data being displayed.

We think Bandlines add real value, so hats off once again to Stephen, and we’re pleased to say that Bandlines are now available in the current version of XLCubed (see here for more detail).

The screenshots below show two examples, displayed in two colour schemes.



The charts depict historic margin by store. The ‘Banding across all stores’ charts show the 30-day trend for the individual store, set in the quartile context of the data for all 11 stores in the table. We can see that for the Gilroy store in row 1, while the margin has varied, it remained in the top quartile when set against all stores for almost the whole period.

The ‘Banding by store, 90 days’ charts show the individual 30 day trend, set in the context of the previous 90 days for the individual store. This helps provide much more historical context, but the line itself still focuses on the more recent trend. Stockton is probably most noteworty here as across the 30 day period it has dropped from the top quartile into the 1st quartile across the whole 90 day period.

We’d love to hear your thoughts (and also which colour scheme works best!), we will also be adding Sparkstrips in the near future so watch this space.