New Features, New Product Fun with v8.5 Release

iDashboards v8.5 is about to be released! New product releases are a big deal when you work at a software development company (around here, we are now saying ‘8.5!’). Many tasks need to be managed, executed and held to a tight timeline. In addition, all employees must be expert product users of the software…at the time of launch.

After having my hands on the ‘beta’ internal version of the software for a few months, I’ve been able to see all the new features get constantly fine-tuned. We have found that the new features are ‘nice,’ some are ‘pretty cool’ and the flagship features are deemed ‘awesome.’ I imagine both existing  and new users of iDashboards will be attracted to different features in the release of v8.5.

As an expert user, I have really become smitten with our new Point-and-Click Chart Designer. The new Chart Designer is a more unified and streamlined experience overall, and more advanced. I am experiencing a dramatic decrease in time when creating charts with this new Chart Designer. For example, it is not unusual for me to build a basic Bar Chart within 10-15 seconds, 20-30 seconds if I need to add filters and 30-60 seconds if the chart also needs to be visually customized (yes, I timed myself). Below is a quick example to show how the new point-and-click Chart Designer can streamline the chart building process.

For new users of iDashboards, I think there will be a natural attraction to our flexible viewing options, capable of delivering dashboards with our traditional Adobe Flash interface or the new HTML5 interface.  iDashboards now has the highest quality HTML5 dashboards on the market, and this is only our first release with HTML. This option will eventually eliminate the need for apps and will certainly allow our mobile users to have a better experience viewing dashboards. Below is a dashboard comparison between the Flash and HTML5 interface.

New or existing users should not ignore what is the most advanced, flexible, creative and custom chart in the dashboard industry: the Image Plot Chart. This is not a traditional analytics chart, but instead a platform for building your own chart by layering dynamic points on any custom image. Now, our users can build their own custom GPS maps, interactive illustrations and more. Below are some examples of what’s possible with the Image Plot Chart.





























Ken Rose – Product Marketing Leader, iDashboards

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Beware of Scale Bias – and Prevent It with Interactive Intelligence

On the road, I often see some amazing dashboard designs. Sometimes when we make charts and graphs though, we combine too much information into one chart. I regularly see charts that have measurements of many items against one X axis. See the chart below for an example of this – the number of people in a city and the amount of rain (in centimeters) the city has had in the last year.





We can see that the number of people in the city greatly exceeds the number of centimeters of rain.  When we put this into a chart, it looks like this:









Image Caption: Left out of the rain, it makes it look like these cities are all in arid climates and didn’t receive any rain at all.

The above chart renders the data as it should, and displays the information; however, this chart really does not do a decent job showing if there is a correlation between the amount of rain a city receives and its population. This makes a classic case for a need of the iDashboards Interactive Intelligence feature. I like to tell my course participants that if a scale bias is introduced into the dashboard decision-making process, the consequential choice might be a poor one if the decision-maker sees a chart like this. What would happen if emergency water rationing went into place in a city that was actually experiencing a flood year as a result of this chart?

Instead, we apply chart object recycling, and we can now see the same chart, but with one “Y.”

We took the chart above, and in the middle frame created these charts:

Left: X of City, Y1 of Population (Hidden), Y2 of CM of Rain (Hidden) Y3: an expression to compute population numbers to rain
Middle: X of City, Y1 of Population
Right: X of City, Y1 of Rain in CM

Now this dashboard tells a story! We can see that even though Denver received the least amount of rain, it also has the highest population, indicating that this city is in real trouble. We can make that correlation somewhat easily by looking at the chart at the right to show rainfall, and the chart at the left that shows us how many people are counting on a single centimeter of rain. A single chart tells facts, but a whole dashboard tells a story.
Dashboard on!

Brad Hines – Sr. Technical Consultant, iDashboards

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Before the Browse: Dashboard First Impressions

iDashboards allows organizations to deliver unique experiences to every user – charts and dashboards they get to see and how they can be edited. Too often, though, little thought is given to what users see even before they begin to browse their available dashboards.

A Startup Dashboard is like a user’s homepage – it is the dashboard that is automatically loaded when a user signs in. Since user needs differ, a Startup Dashboard is a personal setting, configured through the User Settings screen.

By setting up a Startup Dashboard, users can save time and clicks, starting their days off more productively. For example, immediately upon login, a CEO could be viewing an Executive Scorecard while an IT Analyst could be focused on Helpdesk Tickets.

What if a user needs to look at three dashboards every morning? There is only one Startup Dashboard, but users can also bookmark dashboards and make use of dashboard launcher panels to have their favorites just a click away.

These are a few different ways to put important metrics in front of the right users faster. What has worked for your organization? Let’s hear it in the comments.

Warren Singh – Sr. Technical Consultant, iDashboards

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A New Way to Drilldown Hierarchies through Input Parameters

As a consultant for iDashboards, I work with customers to help build their dashboard solutions. Along the way, they never cease to surprise me with creative new challenges and ideas for their dashboard designs. During one of my recent trips, I was able to create a new way of drilling down through a client’s hierarchy of data using our “Change Dashboard Parameters” drilldown. In the data, they had pre-calculated aggregate scores assigned to managers throughout the company, with each individual linked to his or her own manager and direct reports through a “parent-child” type data structure. There was a column for each employee’s ID number and a column with his or her manager’s ID number. An organization’s employee structure isn’t always a fixed number of levels from top to bottom, creating a challenge when I tried to use our chart-to-chart drilldown function on this data structure. In this blog, I’ll explain how I overcame this challenge using the drilldown to change dashboard parameters.  **If you would like review how a regular drilldown works, check out Jerry’s post about drilldowns: “Getting Down to the Nitty-Gritty

During my engagement I had data that looked similar to this:

Because this is not the typical data structure we use for drilldowns, I had to think outside the box. I had to create a drilldown structure that could have a varying number of levels. One person reporting to the CEO could have four levels of management under them, while another individual could have ten. Instead of creating ten charts, I was able to create a dashboard that only uses two charts for infinite drilldown capability (it only stops at the end of the hierarchy). This solution contains the following elements:

1. One chart that will drilldown the hierarchy

2. One chart that will drill back up

3. A dashboard input parameter for filtering on the “parent” value

Here is an example of a dashboard built with the sample data containing these elements:


In chart #1, I have used the input parameter to filter the information where the “Manager Name” column in my data is equal to the Manager selected in the input parameter. My X-axis uses the “Name” column for its values; therefore, I am showing the scores of the direct reports for the selected manager.  I set my x-axis label to “Manager” because the x-axis label must match the name of the input parameter in order for the drilldown work. So if I click on the CFO, I will drilldown to see the positions that report to the CFO.

In chart #2, I used the ViFrame chart type to display text showing who the selected manager reports to. This is the chart that will take us back to the previous manager after we have drilled down. I still use the input parameter as a filter, but this time I filter on the “Name” column instead of the “Manager Name” column in my data. For my X and Y labels, the axis labeled “Manager” is now mapped to the “Manager Name” column.

The chart labeled #4 is not part of the drilldown, but an extra chart I created so that I could still see the information about the manager I selected. It is built exactly like chart #1, but I filtered it the same way as chart #2. You can see my input parameter placed at the top of my dashboard, so I can skip down the list without drilling if I choose to. Whenever I click in chart #1 or #2, it will place their value into the input parameter and change its own filtering, creating a sort-of circular logic. After creating your charts, you only have to set up the drilldown by going to the Chart Properties and selecting the drill down:

If everything has been set up correctly, then congratulations! You should now be able to drill up and down your data:

This technique works for ANY kind of data hierarchy you have where you varying levels of detail.  Maybe instead of a corporate structure, you may be dealing with Regions and varying levels of sub-regions. The possibilities are limitless.

Just remember – the data must be formatted in a “parent-child” format similar to my sample data above. As a general rule, most – if not all – aggregation that your data may need (sums, averages) will have to be done ahead of time at the data source, depending on your desired results.

I hope this has been a helpful and informative article for you. Now go, take this technique and see what kinds of new powerful insights you can find.

Alex Stark – Technical Consultant, iDashboards

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Code Red

The cover of the March 10, 2014 issue of the TIME magazine was called “Code Red”. The cover story announces: “How an unlikely group of high-tech wizards revived President Obama’s troubled website.” As the topic, Affordable Care Act or Obamacare is very controversial in this country, I want to point out that this blog is not about the merits of this new law. It is about one certain aspect in particular that was critical in this successful “rescue mission.”

Well, you might have already guessed it, one of the first things that those high-tech wizards did to determine what kind of problems they are dealing with was to create a dashboard. “Among many jaw-dropping aspects of what we found, as one put it – was that the people running had no dashboard.” When the website was launched, nobody knew how many people were using the site, the response times for various click-throughs were unknown and it was not clear where the traffic was getting tied up. I don’t know about you, but those are the things that I would like to know if I were to launch my own website. One more thing worth mentioning is that those tech wizards built a dashboard in about 5 hours.

Of course there were other mechanisms put in place for this rescue mission, but a dashboard was put in place right away and was an essential part of recognizing the scope of the problems. Based on the dashboard, the high tech wizards could make a decision about whether the website could be fixed or not. We all know at the end the website was improved to a point where millions of people were able sign up for health insurance.

You probably agree with me that for a project of this magnitude, a dashboard is vital to the success of the project. But, what about other projects that are smaller in size? We live in an era where there is an overload of data and the best way of “slicing and dicing” data is with visualization tools. So my argument is no matter what size of the project, dashboards can help you to get a high level of understanding your data very quickly and, as pointed out in the example above, dashboards can help you pinpoint problems in a very dynamic way.

By the way, I am pretty sure that with the right tool, those tech wizards could have created that dashboard in half of the time. 

Aziz Sanal – Technical Consultant, iDashboards

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Back to Basics

The more I talk to people about anything Business Intelligence, the more buzz words I get to hear e.g. Big Data, Prescriptive Analytics, Hadoop, YARN, Pig, etc. For most SMBs that I talk to, however, (humbly putting) these terms are more just buzz words. Don’t get me wrong, the innovation needs to happen and is happening. Go to any BI (Business Intelligence) event in the country and you will see the signs of innovation. However, you may also notice that basic topics like BI adoption, BI project success criteria, BI project anatomy and proactive performance management are a regular part of the event. What does this tell us? With the continuous and fast changes in technology, these basic things still need attention and priority, and that is where I wanted to bring the focus to.

The techies may seem very enthusiastic as to what technology can do for the business. And vice-versa business people may seem very excited about implementing new technology. It is something and someone in between that could bring the business vision and the technology together. Project managers play an important role in this regard, unfortunately it is an overlooked area. People might take shortcuts and it may cost organizations lot more in the long run.

 As BI becomes more and more available to every level in the organization and to the masses, the need to focus on the core deliverables becomes more important. When I talk to these organizations I still hear that simple reports, analytics, dashboards and other basic BI deliverables still remain challenges to implement and to maintain. There is alot of help available in the market to tackle these basic needs. There are more agile, robust, dynamic, easy-to-use tools available that can be utilized to help achieve the goals.

Let’s commit to better BI foundation. Let’s evaluate where we are and what our basic core goals, and build from there. Shall we?

Zahid Ansari – Pre-Sales Manager, iDashboards

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Limitations: Misunderstood

Limits can be subject to mathematic calculations, sequence, function, time, space, speed, weight, age, scientific, engineering, legal, technical, language, emotional…

Some limitations are subject to personal or technical capability, such as earning potential or hard drive space.  Over time, however, these limits have the potential to increase, and for different reasons!  Most limits related to technology evolve over time and increase at a staggering rate.  Remember the early hard drives and RAM specifications?  Year over year it made sense to develop new technology to sustain the growth for faster and larger computers.

Some limits don’t need to increase over time.  For example, since being a teenager, I continue to buy cars with higher maximum speed limits.  But the roads I drive on continue to post the same speed limit.  Therefore, my car has a different maximum speed limit compared to the roads where I drive (contrary to my desire to drive faster).  I also have a desire to limit my weight gain, which doesn’t need to increase over time.

I think it is important to understand there are different types of limits.  When I think about limits, I realize that some can change and some cannot, or should not.  It takes some research and understanding to learn about limits before a conclusion can be developed.

There are endless types of limitations.  My goal is to discuss a specifically defined limitation within an iDashboards chart.  It is really more of a helpful visual aide and not a limitation.  Regular charts within iDashboards have a 1,000 row limit, and pivot charts have a 3,000 row limit.  There, I said it.  Phew.  During the development of iDashboards, we have purposely defined these limitations.  Let me further explain the limitation.  An iDashboards chart will query your data source (Excel, SQL, database, other…) and collect a result set.  The chart has a row limitation on the result set, not the data source.  iDashboards does not have a limit on how much data can be queried in your data source.

For example, imagine you have data with 1-million rows.  During the chart creation process, you set up the query to obtain ‘The total sales for all products’.  Because you have 4 products, your result set will return 4-rows.  If you have 103 products then your result set will return 103-rows.  Essentially, we are trying to summarize the information to make it digestible and capable of being presented through graphs and charts.  Therefore, using filters, functions (SUM, AVG, etc.), input parameters, drilldowns or pivots, allows you to specify the exact amount of data.

Because iDashboards is a data visualization technology, we offer visually engaging ways to display a result set.  With iDashboards, each row of the result set is displayed as a column, point, pie-slice, indicator color, image, etc.  Visually speaking, you shouldn’t want to display more than 1,000 rows of data in a chart.  Don’t you agree?  Without a row limitation, there is too much data and the visual purpose becomes unusable.  Most computer screens have a maximum width between 1400-1920 pixels.  Having a Column Chart with more than 1000 columns makes it nearly impossible to distinguish the graphic since each column would be 1x pixel wide.

Here are some references for learning about how to reduce the data in your chart:

If you’re still not convinced a row limitation is useful, here are some pictures.  So, what does 1,000 data points look like within a chart?

A Column Chart with 1,000 columns (aka ‘1,000 rows of data’)


A Bar Chart with 1,000 bars (aka ‘1,000 rows of data’)


A Scatter Plot Chart with 1,000 points (aka ‘1,000 rows of data’)


A Metrics Chart with 1,000 indicators (aka ‘1,000 rows of data’)


A Pie Chart with only 72 slices (aka ‘72 rows of data’)


Ken Rose – Product Marketing Leader, iDashboards

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What is the Purpose of a Chart?

iDashboards has the most variety of charts in the industry. This can make choosing the right chart a little overwhelming. To help in selecting the best chart, I ask myself, “What story does the chart tell?” In other words, what is the purpose of the chart?

Below is a table suggesting what chart type to use based on the chart’s purpose:

To give credit where due, this table started from the list, Chart Selection Process. I added some recommendations and iDashboards specific chart types to broaden your scope. If you see some chart types you are unfamiliar with, iDashboards OSKAR forum users can download examples here. Otherwise, send a reply below and I’ll provide you some samples.

I hope this helps you get creative with your charts and always create Powerful Insights.

Paul Ligeski – Senior Consultant, iDashboards

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Getting Down to the Nitty-Gritty

On my daily commute, after one of Michigan’s most brutal winters, I have the opportunity to encounter multiple pot holes. Those nasty, alignment-altering holes that go deeper and deeper from the surface until they get to the nitty-gritty layer that was once the original surface.

Drilldowns in a dashboard work much in the same way. In a drilldown, you are moving from one layer to another, ultimately working your way down to the nitty-gritty information you are looking for.

In creating a successful drilldown, there are a number of things to consider.

Start with the source chart for your drilldown. Let’s say we start with a column chart showing sales figures tallied by country. When designing the drilldown target, which will show Sales by City for the selected Country on the source chart, I will start with the original source chart side-by-side, because I will use many components of the source chart for the drilldown target.

In what will be the target chart, I right click, choose Chart Data and Cut and Paste my original x-axis as a new y-Axis label. I will use this label copied to the clipboard again shortly. I now put in my new x=axis label of City, as shown in Image 1.


With the new x-Axis, it is a quick trip through my data source connections (assuming we’re working from one data source) to the point where I now map my new x-axis to City and my newly created y-Axis to Country. I also now create a pivot on Country as shown in Image 2.



Once the target chart is created I like to change the chart to differentiate it from the source to give the visual appearance of change. This chart will ultimately be a chart filtered by City for the selection made at the Country level.


At this point I save the new chart by right clicking and choosing Save Chart As to choose the new chart name. I save the chart with a Sales by City name, and make the chart title Sales by City from ${value:Country} (this is where I can paste the filtering selection from my original cutting of the x-axis label from earlier). That label from the pivoted y-axis needs to match the Value Macro in order for it to work in the title of the target chart.

The final step in creating the filtered drilldown is to go into the Chart Properties on the source chart and choose the Drilldown tab and the Drilldown to Chart option from that tab. See Image 4.



Note the simplicity of creating a drilldown. The application understands which axis values need to be sent to the target chart automatically. The x-axis of Country is automatically selected when the drilldown is chosen.

Now, when the chart is saved and the drilldown selection is made, the target chart appears and is filtered for the selection that is made (Image 5). Also, note that the Country label is shown in the title, so we know which country we selected by looking at the filtered chart.



At this point we can do one more level of filtering to get to our granular details of knowing how many units have been sold per city (the nitty-gritty details!).



We see that again in the chart title, we’ve pulled in the selected values for both Country and City. This has been accomplished by using the following syntax in the chart title – Units Sold  – ${value:Country}, ${value:City}.

It’s no surprise that drilldowns are invaluable in the world of iDashboards. This was after all only one of the many type of drilldowns available. It’s a matter of how you want to show your filtered metric. We could have just as easily set up a drilldown to a dashboard, to a report, or to a website. It all depends on how you wish to see the nitty-gritty details of your data.

Jerry Stowe -Senior Technical Consultant

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Advanced Filtering Technique

In this blog, you will learn an advanced filtering technique with the ‘Data Source Column’ method.

Image 1 below shows a sales dashboard with 5 input parameters as follows:

• Start Date
• End Date
• Product Line 1
• Product Line 2
• Product Line 3

The three controls for Product Lines allow a user to either select ‘ALL’ in the first, or up to 3 distinct values to filter the dashboard. If you are a well experienced iDashboards user, you may notice a typical roadblock here, “how can I have an ‘and’ as well as an ‘or’ operator in the ‘WHERE’ clause using the data source column method?”

Image 1

The standard method when creating input parameters for filtering purposes is that each input parameter results in one filter referencing that input parameter. So, assuming this to be true and knowing that each of the charts on this dashboard have 5 parameters, we can conclude that there are at least 5 filters.

Image 2 shows our list of input parameters on the charts, but if we take a look at the filters, we would expect to see at least 5 filters including the 5 for the input parameters.

Image 2

In looking at Image 3, this is not the case. Rather, there is only one filter which includes reference to each on the 5 input parameters. The ‘Filter’ interface is simply used to create the ‘WHERE’ clause in the SQL Query that iDashboards is configuring for the chart. What this means is that you can simply use one filter to configure more complex filter criteria than simply creating a unique filter for each input parameter and also can combine ‘And’ as well as ‘Or’ operators without needing to use custom SQL.

Image 3

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