Excel Dashboard Software

When used properly, dashboards are highly effective business intelligence tools. However there are many mistakes that can be made when designing a dashboard,  that can ultimately result in a less effective and sometimes even confusing layout.

Some of the primary things to avoid when creating dashboards are:

• Clutter
• Lack of Focus
• Irrelevant charts

• Clutter:

When you design your Excel dashboard you should keep in mind that you want reports that are clear, succinct and to the point. What you definitely do not want, is a dashboard that is so full of various charts and data that it is impossible to get a clear overview.

• Lack of Focus:

To create an effective dashboard, the designer must first know exactly what information he or she wants to receive from the dashboard. There is no point including a chart on the amount of water purchased for the staff canteen, or the figures spent on a specific advertising campaign, when this sort of data can be included in more general charts focussed on expenses. If you want that kind of specific detail, you can include it through drill down features, or even create a separate dashboard for detailed expenses. Always remember that a dashboard should display KPIs (Key Performance Indicators), that help managers and executives decide what changes and decisions should be made to boost the company’s performance. The designer of the dashboard therefore needs to know exactly what the KPIs are, so that the dashboard can reflect the relevant information.

• Irrelevant Charts

Again this is a very key error that can easily happen when putting together an Excel dashboard. Even small business generate a huge wealth of information, and just about any aspect of a business’ day-to-day operations can be charted and potentially included in a dashboard. It is therefore necessary to be clinically precise when creating your dashboard. Remember you can always go back and edit the specifications if you find that you have included certain charts that are irrelevant to your decision making, or if you have omitted data that is highly important. Business intelligence software such as an Excel dashboard can make an immediate difference to how you run your business, but it is important to constantly adapt your software to your needs and to your operation.

Let say you have your data in the following format

 

 

 

 

 

 

 

The column represents the year. Let us not concern about the other columns for now.

How can we represent the data above as below which shows the data grouped by the year where the current row year is added to only the next row year. Every row, looks ahead , get the next year value and sums it up and shows as a unique row.

 

 

 

 

So the end result should be a pivot table that has 2008 and 2009 values summed up, 2009 and 2010 summed up.

Assuming there is no direct relationship between 2008 and 2009 we will try to derive algebric relation and see if we can get the desired result.

The solution assumes that there will be a starting year provided as a seed value. so in this case we will consider 2001 as the seed value.

On the dashboard, we can create a parameter so that we don’t have to hard code the value 2001

Take a look at the below screenshot

 

 

 

 

 

 

 

The different columns are mod calculations to derive the final relation on how the alternative rows can be related.

Once we get a common value or the relation value, we can easily sum them up in the SQL

The first mod operation between Year and 2001 (fixed value or seed value) gives us sequential numbers

The second mod operation on top of the first mod gives us 010101 sequence.

So now looking at the pattern, if we subtract the second mod operation value from the first mod value, we get the column Diff

So now, 2001 and 2002 are related because their calculated diff value is 0, so are 2003 and 2004

But we also need rows that represent the sum between 2002 and 2003, 2004 and 2005 and so on. The above logic is missing those.

In our calculation if we add the two mods, we get below

 

 

 

 

 

 

 

Now, we have years (2002,2003), (2004,2005), (2006,2007) related.

So in our query, if we join the two SQL using union then we can expect to see all the row combinations

Now let us implement it on the dashboard.

The sample excel file is as shown below

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We will connect to this excel file and pull this table on the dashboard (Check this tutorial how to connect excel file)

here is the screenshot of the excel file on the dashboard

 

 

 

 

 

 

 

 

 

 

Next we split the date column into year and month columns

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We select the year and month columns (need to scroll down when selecting month)

So we get the table (qlet) as below

 

 

 

 

 

 

 

 

 

 

NOTE: We can manually change the month format to remove the first two digits. for e.g 01-Jan to just “Jan”. We edit the query and update the following line format(”some_date”,’mmm’) as “so_Mth_Disp”, (we just added an extra m and remove the other format)

We also add the following columns mod1, mod2, related field, r1 and r2 which are explained below

<code>

select
“some_date”,
year(”some_date”) as “so_Year”,
“so_Year” – 2001 as “mod1″ ,
mod1 – fix(mod1/2)*2 as mod2,
mod1 – mod2 as “related_field”,
related_field + 2001 as r1,
related_field + 2001 + 1 as r2,

format(”some_date”,’mmm’) as “so_Mth_Disp”,
format(”some_date”,’yyyy-mm(mmm)’) as “so_Yr_Mth_NN”,
format(”some_date”,’q') as “so_Qtr”,
format(”some_date”,’yyyy-ww’) as “so_Yr_wk”,
datepart(’y',”some_date”) as “so_Yr_Dy” ,
“some_amount”
From (Select
she.”some_date” ,
she.”some_amount”
From
[Sheet1$] she
) as dateColsx

</code>

Since Excel odbc does not support the mod function, we use division and multiplication to arrive at the mod value

We have hard coded the value to 2001 but we can always replace this with the parameter from the dashboard which we will do it at the very end.

Having all the related columns derived based on our excel model earlier now it is time to work on the month columns. Since all the dates are rows, we need to somehow show them as columns.

First step is we use the switch statement to separate each month into a column.

here is the SQL with the switch statement

<code>

select “so_Year”, r1&’ — ‘&r2 as yr
,switch(so_mth_disp = ‘Jan’, some_amount, so_mth_disp <> ‘Jan’,0) as “m1″
,switch(so_mth_disp = ‘Feb’, some_amount, so_mth_disp <> ‘Feb’,0) as “m2″
,switch(so_mth_disp = ‘Mar’, some_amount, so_mth_disp <> ‘Mar’,0) as “m3″
,switch(so_mth_disp = ‘Apr’, some_amount, so_mth_disp <> ‘Apr’,0) as “m4″
,switch(so_mth_disp = ‘May’, some_amount, so_mth_disp <> ‘May’,0) as “m5″
,switch(so_mth_disp = ‘Jun’, some_amount, so_mth_disp <> ‘Jun’,0) as “m6″
,switch(so_mth_disp = ‘Jul’, some_amount, so_mth_disp <> ‘Jul’,0) as “m7″
,switch(so_mth_disp = ‘Aug’, some_amount, so_mth_disp <> ‘Aug’,0) as “m8″
,switch(so_mth_disp = ‘Sep’, some_amount, so_mth_disp <> ‘Sep’,0) as “m9″
,switch(so_mth_disp = ‘Oct’, some_amount, so_mth_disp <> ‘Oct’,0) as “m10″
,switch(so_mth_disp = ‘Nov’, some_amount, so_mth_disp <> ‘Nov’,0) as “m11″
,switch(so_mth_disp = ‘Dec’, some_amount, so_mth_disp <> ‘Dec’,0) as “m12″

from
(
select
“some_date”,
year(”some_date”) as “so_Year”,
“so_Year” – 2001 as “mod1″ ,
mod1 – fix(mod1/2)*2 as mod2,
mod1 – mod2 as “related_field”,
related_field + 2001 as r1,
related_field + 2001 + 1 as r2,

format(”some_date”,’mmm’) as “so_Mth_Disp”,
format(”some_date”,’yyyy-mm(mmm)’) as “so_Yr_Mth_NN”,
format(”some_date”,’q') as “so_Qtr”,
format(”some_date”,’yyyy-ww’) as “so_Yr_wk”,
datepart(’y',”some_date”) as “so_Yr_Dy” ,
“some_amount”
From (Select
she.”some_date” ,
she.”some_amount”
From
[Sheet1$] she
) as dateColsx
)

</code>

here is the resulting table

 

 

 

 

 

 

 

 

 

 

 

 

 

If you notice we concatenated r1 and r2 to create a single new column and we named it as ‘Yr’

Finally we sum all the month columns and group by the new ‘Yr’ column

select yr,
sum(m1) as jan,
sum(m2) as feb,
sum(m3) as Mar,
sum(m4) as apr,
sum(m5) as may,
sum(m6) as jun,
sum(m7) as jul,
sum(m8) as aug,
sum(m9) as sep,
sum(m10) as oct,
sum(m11) as nov,
sum(m12) as dec
from
(
select “so_Year”, r1&’ — ‘&r2 as yr
,switch(so_mth_disp = ‘Jan’, some_amount, so_mth_disp <> ‘Jan’,0) as “m1″
,switch(so_mth_disp = ‘Feb’, some_amount, so_mth_disp <> ‘Feb’,0) as “m2″
,switch(so_mth_disp = ‘Mar’, some_amount, so_mth_disp <> ‘Mar’,0) as “m3″
,switch(so_mth_disp = ‘Apr’, some_amount, so_mth_disp <> ‘Apr’,0) as “m4″
,switch(so_mth_disp = ‘May’, some_amount, so_mth_disp <> ‘May’,0) as “m5″
,switch(so_mth_disp = ‘Jun’, some_amount, so_mth_disp <> ‘Jun’,0) as “m6″
,switch(so_mth_disp = ‘Jul’, some_amount, so_mth_disp <> ‘Jul’,0) as “m7″
,switch(so_mth_disp = ‘Aug’, some_amount, so_mth_disp <> ‘Aug’,0) as “m8″
,switch(so_mth_disp = ‘Sep’, some_amount, so_mth_disp <> ‘Sep’,0) as “m9″
,switch(so_mth_disp = ‘Oct’, some_amount, so_mth_disp <> ‘Oct’,0) as “m10″
,switch(so_mth_disp = ‘Nov’, some_amount, so_mth_disp <> ‘Nov’,0) as “m11″
,switch(so_mth_disp = ‘Dec’, some_amount, so_mth_disp <> ‘Dec’,0) as “m12″

from
(
select
“some_date”,
year(”some_date”) as “so_Year”,
“so_Year” – 2001 as “mod1″ ,
mod1 – fix(mod1/2)*2 as mod2,
mod1 – mod2 as “related_field”,
related_field + 2001 as r1,
related_field + 2001 + 1 as r2,

format(”some_date”,’mmm’) as “so_Mth_Disp”,
format(”some_date”,’yyyy-mm(mmm)’) as “so_Yr_Mth_NN”,
format(”some_date”,’q') as “so_Qtr”,
format(”some_date”,’yyyy-ww’) as “so_Yr_wk”,
datepart(’y',”some_date”) as “so_Yr_Dy” ,
“some_amount”
From (Select
she.”some_date” ,
she.”some_amount”
From
[Sheet1$] she
) as dateColsx
)
)
group by yr

Result

 

 

 

 

 

This almost looks like what we needed but it is missing the rows 2002 — 2003, 2004 — 2005 etc

We simply edit the SQL, duplicate it and append to the same SQL as a union query. The only difference would for the bottom union is that the related_field would be the addition of mod1 and mod2

select yr,
sum(m1) as jan,
sum(m2) as feb,
sum(m3) as Mar,
sum(m4) as apr,
sum(m5) as may,
sum(m6) as jun,
sum(m7) as jul,
sum(m8) as aug,
sum(m9) as sep,
sum(m10) as oct,
sum(m11) as nov,
sum(m12) as dec
from
(
select “so_Year”, r1&’ — ‘&r2 as yr
,switch(so_mth_disp = ‘Jan’, some_amount, so_mth_disp <> ‘Jan’,0) as “m1″
,switch(so_mth_disp = ‘Feb’, some_amount, so_mth_disp <> ‘Feb’,0) as “m2″
,switch(so_mth_disp = ‘Mar’, some_amount, so_mth_disp <> ‘Mar’,0) as “m3″
,switch(so_mth_disp = ‘Apr’, some_amount, so_mth_disp <> ‘Apr’,0) as “m4″
,switch(so_mth_disp = ‘May’, some_amount, so_mth_disp <> ‘May’,0) as “m5″
,switch(so_mth_disp = ‘Jun’, some_amount, so_mth_disp <> ‘Jun’,0) as “m6″
,switch(so_mth_disp = ‘Jul’, some_amount, so_mth_disp <> ‘Jul’,0) as “m7″
,switch(so_mth_disp = ‘Aug’, some_amount, so_mth_disp <> ‘Aug’,0) as “m8″
,switch(so_mth_disp = ‘Sep’, some_amount, so_mth_disp <> ‘Sep’,0) as “m9″
,switch(so_mth_disp = ‘Oct’, some_amount, so_mth_disp <> ‘Oct’,0) as “m10″
,switch(so_mth_disp = ‘Nov’, some_amount, so_mth_disp <> ‘Nov’,0) as “m11″
,switch(so_mth_disp = ‘Dec’, some_amount, so_mth_disp <> ‘Dec’,0) as “m12″

from
(
(
select
“some_date”,
year(”some_date”) as “so_Year”,
“so_Year” – 2001 as “mod1″ ,
mod1 – fix(mod1/2)*2 as mod2,
mod1 – mod2 as “related_field”,
related_field + 2001 as r1,
related_field + 2001 + 1 as r2,

format(”some_date”,’mmm’) as “so_Mth_Disp”,
format(”some_date”,’yyyy-mm(mmm)’) as “so_Yr_Mth_NN”,
format(”some_date”,’q') as “so_Qtr”,
format(”some_date”,’yyyy-ww’) as “so_Yr_wk”,
datepart(’y',”some_date”) as “so_Yr_Dy” ,
“some_amount”
From (
Select
she.”some_date” ,
she.”some_amount”
From
[Sheet1$] she
)
as dateColsx
union
select
“some_date”,
year(”some_date”) as “so_Year”,
“so_Year” – 2001 as “mod1″ ,
mod1 – fix(mod1/2)*2 as mod2,
mod1 + mod2 -1 as “related_field”,
related_field + 2001 as r1,
related_field + 2001 + 1 as r2,

format(”some_date”,’mmm’) as “so_Mth_Disp”,
format(”some_date”,’yyyy-mm(mmm)’) as “so_Yr_Mth_NN”,
format(”some_date”,’q') as “so_Qtr”,
format(”some_date”,’yyyy-ww’) as “so_Yr_wk”,
datepart(’y',”some_date”) as “so_Yr_Dy” ,
“some_amount”
From (
Select
she.”some_date” ,
she.”some_amount”
From
[Sheet1$] she
)
as dateColsx

)
)

)
group by yr

In this article we will take an Excel source containing scorecard information and convert into dials and speedometer charts.

We will also create few bar trending charts.

Consider the below sample data

Source File: You can download the excel file here

 

 

 

 

The above excel file tracks few metrics such as safety, quality and revenue. This is just a sample data and may not make sense in actual world but just imagine a manufacturing company that wants to track its overall safety and quality score and also track its total revenue. Now the company may use its own method at deriving the individual safety and quality scores.

They may have a dedicated team to collect safety violations and product defects and then use some formulae to convert those data into final score for any given month. We are not concerned with any of the methods on how those scores are generated. You are the dashboard person and the company has provided you the metrics by each month and now your job is produce a nice dashboard that shows relevant charts for the given data.

Since the data is tracked for each month, it makes sense to show a line or bar chart trending for the metrics.

Dials and Speedometers are relevant when we need to show performance of a single value. So in this case, since we have 12 month data, how do we show single value on the meter chart?

One solution is to show an ‘Average’ value for the safety and Quality metrics or we could show a dial that shows the current month values.

So the GOAL for this exercise is: Show bar chart for Safety trending 12 months and show average and current month value on the dial chart.

Dial chart requirement: For the dial chart, we are measuring the performance, whether we are on track or missed the goal. In order to achieve that, we create three new columns for safety such as ’safety_bad’, ’safety_ok’, safety_good’. These values need to be decided by the company management. If you are not sure, then look at previous year data and decide what should be good and bad values. The dials are used to guide the company to perform better or atleast improve that portion of the company operation represented by the metric.

 

 

 

 

 

 

 

First let us create the date hierarchy columns from the Period column. You need to make sure that the Period column is an actual Excel date column, else the hierarchy will not be generated

 

 

 

 

 

 

 

 

 

 

Right click on the period column, select Create -> Add Year, Quarter, Month columns

 

 

 

 

 

 

 

 

 

 

As you see we added the year and month columns. We may not use all of the above columns but having them ready gives us the option during the chart building.

Now right click on the “Name” and select ‘Create Chart”

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We selected the ‘Bar’ chart type

For the x-axis we select the month column and for the y – axis we select the Safety metric

Next, we click on the “Create Chart” button

This action takes us to the below dialog

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We rename the chart to ‘Safety’ and then click on ‘Fully Apply’

This action create the below chart (You may need to move the screens and dialog around to see the chart behind)

 

 

 

 

 

 

 

 

 

 

Now having the chart wizard open, we change the selection to ‘Dial’ chart

Check the Dial chart options below

 

 

 

 

 

 

 

 

 

We modify the options as below

• You can type the low and high range values for each range on the dial.
• In our case, we have defined the safety bad, ok and good values in our spreadsheet so when our goals change, we just change the spreadsheet and the dials will automatically take care. Also, what if we needed different goals for each month so rather than hard coding the range in the chart, we get them from the excel file

 

 

 

 

 

 

 

 

 

 

 

 

We first change the label sequence for the “Region Name” from “Bad” -> “Warning” -> to “Good”. For the dial chart the labels are not used so make sure that the colors are selected appropriately.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

You may click on the color icon to change the colors of your choice

Next, we select the range boundary values

 

 

 

 

 

The safety_bad value from our spreadsheet represents the lower boundary of our bad region, “safety_ok” represents the upper boundary of our bad region, similarly ’safety_ok’ is the lower bound for our ‘ok’ region and so on. For the ‘Good’ upper bound we simply typed a value but as general practice we should have one more column for the upper bound of the final region. In our case the final region is ‘Safety Good’.

Next, for the pointer value, select the column that you want to show on the dial chart. In our case we select ‘Safety’ and aggregation as ‘Avg’

 

 

 

 

 

 

Next, we click on “Create chart”. This action shows the dialog below

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We change the chart title to ‘Average Safety’

NOTE: remove the double quotes in the SQL statement for the group by. This will cause an error.

Click on ‘Fully Apply’

Here is our final Dial Chart

 

 

 

 

 

Next, create a dial chart to show current month value

We will change some conditions on the main Qlet. Right click on the “Name” and select ‘Duplicate’

 

 

 

 

 

 

 

 

It creates an exact copy of the qlet table. We change the name to ‘Current Month’

 

 

 

 

 

Right click on the ‘Period’ column and select ‘Create’ -> Create Date Filter

 

 

 

 

 

 

 

 

 

 

This action shows a dialog as shown below

 

 

 

 

 

 

 

First change the operator to ‘Between’

Next select ‘First Day of Month’ for the from and ‘Last Day of Month’ for the To val.

Click on ‘Use This Filter’

This action applies the filter to the Qlet and it shows only currrent month row

 

 

 

 

 

 

 

 

 

 

 

Next, right click on ‘Current Month’ and select ‘Create Chart’

All of the settings remain the same except the ‘Aggregation’, make sure to select ‘NONE’

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Once all the three charts are done, we arrange them as below

 

 

 

 

 

 

 

 

Similarly, you may create the charts for “Quality” and “Revenue”

When you use the Add Date hierarchy columns for any date, by default it brings all calendar quarter and calendar month.

 

How do you get Fiscal Quarter

Let say your fiscal year begins from 1st July then

First Quarter = { 7 , 8 , 9}

Second Quarter = { 10, 11, 12}

Third Quarter = {1, 2, 3}

Fourth Quarter = { 4, 5, 6 }

So with the above logic let us create a formula

• Right click on the date column
• Select “Create Calculation”
• 
• Type the following formula
• switch(
  month(”Order Date”) in (7,8,9) , ‘Qtr1′ ,
  month(”Order Date”) in (10,11,12) , ‘Qtr2′ ,
  month(”Order Date”) in (1,2,3) , ‘Qtr3′ ,
  month(”Order Date”) in (4,5,6) , ‘Qtr4′
  )
• Click on ‘Use This Formula’

Here is the Fiscal Quarter

Note: You can change the Quarter text to anything like ‘Q1′ instead of ‘Qtr1′

Fiscal Month

Similarly, if you need fiscal month, we can use the following formula

switch(
month(”Order Date”) >= 7 , month(”Order Date”)-6 ,
month(”Order Date”) < 7 , month(”Order Date”) + 6
)

Fiscal Year

switch(
month(”Order Date”) >= 7 , year(”Order Date”) ,
month(”Order Date”) < 7 , year(”Order Date”) – 1
)

 

If you have a different Fiscal year begining then replace the numbers accordingly.

Put your Excel Dashboards on the web

Create your excel dashboards on Desktop and then easily put them on the web or intranet.

Download the web dashboard files

• Web Dashboard Documentation

The documentation is a complete printable reference guide for converting desktop to web dashboard and has a reference section for chart properties to create advanced charts.

Download web dashboard software

• The link to the web dashboard software is provided within the above documentation link.
• download web dashboard software

>Alternative Video Tutorial or Follow the steps below

Sometimes, due to some improper setup of Microsoft Excel or incomplete components for Microsoft Office, direct connection to Excel files may not be possible.

This tutorial provides an alternative method to connect to the Excel Files. This method also applies to any new format of Excel Files or Microsoft Access databases (ie. mdb or .accdb)

Steps to Create DSN for ODBC connection

1. Click on the Start menu and click on the Control Panel

 

2. Click on the “Administrative Tools”.

NOTE: You may need to “Switch to Classic View” in windows Vista or newer version of your windows operating system

 

3. Click on the “Data Sources (ODBC)” setup icon

 

4. Click on “Add”

 

5. Select .xls, .xlsx .xlsm .xlsb option if you are using the latest Excel version and format of Excel

6.We will select the normal .XLS version since this northwind.xls file was created using old format

7. Give a short and simple name to this DSN entry

 

8. Now select and point this DSN name to the appropriate Excel file

9.

10. select the file and click OK. Close all the dialogs.

11. Now go back to InfoCaptor connection wizard

12. Select the “ODBC” option now instead of the “Excel” option

13. Give some simple name to this connection so that InfoCaptor can easily remember it

14. Type the ODBC name that was defined in the ODBC DSN setup screen previously

15.

Click on the Connect button and then you can proceed the remaining of this tutorial after the connection part

Free Dashboard PDF Tutorial

Previous – Excel Dashboard Tutorial – 11

How do you share your Excel Dashboard with users?

Now that you have built the dashboard, you can share the dashboard in multiple ways.

” Create a PDF output of the dashboard and send as email attachment.

Click on the PDF icon on the toolbar as shown below and it will instantly create a PDF output

 

PDF output

 

” Create Static HTML output. Click on the HTML icon on the toolbar. This option creates a static html page that you can put in on the web. Users cannot interact with the dashboard. It is just a snapshot image of the dashboard at the time the output was generated. It does not refresh automatically. You will need to regerate the output again when the data is refreshed.

” Desktop Sharing. You can put the dashboard definition file (icv) on a file share directory and other users can view the dashboard through the Dashboard viewer. You may need separate license for dashboard viewers for desktop.

Go to Menu Create ‘ Publish to web and it will generate a file that you can put it where the dashboard web server is and it will render the output. The look and feel is different with this option

The web version is using a flash charting engine to the desktop Java chart engine.
Details of converting the desktop to web version are not covered in the document. Please refer online at any of our websites for more details

You can download the complete tutorial as PDF
” Web Sharing: In this option, you can publish the dashboard to web and the dashboard is available real time with all the dashboard parameters and refresh actions

Previous – Excel Dashboard Tutorial

Summary

We built the above dashboard completely from scratch.

• We defined Calculations
• We defined date hierarchies
• We built Date Filters
• We built Date Parameters
• We built Bar Charts
• We built Pie Charts
• We cleaned the dashboard layout

Next – Share Excel Dashboard with other Users

Previous – Excel Dashboard Tutorial – 9

Cleanup – Resize and Organize

Give appropriate names to each portlet.
During the chart creation if we did not provide names, now is the time to provide them.
Right click on each title and click on “Edit”

 

Scale down the Size

 

Note, you can drag the corners of each portlet to resize the frames and drag the title name to place them on the canvas

Screen real-estate is very important when designing any dashboard or web application. For better space utilization, we will convert the standard pie to a 3D view

Also, while arranging the objects, keep the most important charts on the top and left area. Put all the detailed portlets at the bottom.

Avoid horizontal scrolling

Remember, do not put any objects on the right side of the scroll bar. Always, keep the scrolling to vertical as it is convienient for viewing.

The above layout will cause for horizontal scrolling and is not a good practice.
Once you do the basic layout of placing the portlets so that they are distinctly visible, it becomes easy to use the resizing options within the tool.

Navigate to Edit ‘ Resize Mode

Once in the resize mode, you can select each object and they are enabled for group resize and placement

Select all the parameters on the top and we will align the top edges with respect to the first one.

As you see, each plet is shown in red with a bar on top indicating it is selected for alignment
One more, thing, you can also turn the Grid mode to see a guide for your alignment and placement

Goto Edit ‘ Show Grid

Note: Once you are done with resize and align with one set of objects, make sure to deselect them before working on the next set of objects

It is best practice to first resize all the objects. All objects on the same horizontal line should have the same height. Select the optimum height of any object on that particular horizontal line and then right click on the title and resize the height of all the selected ones. Then apply the alignment -> Top , deselect the objects and start with the objects in the next horizontal line.

This completes our basic dashboard which is dynamic and extremely informative.
If you need to further customize the look and feel please refer to our online tutorial and reference section
http://www.infocaptor.com/user_help/bi-dashboard-help.htm

Next – Excel Dashboard – Complete Order Management Dashboard

Previous – Excel Dashboard Tutorial – 8

Finish the Dashboard Design and Development

By now, your dashboard is quite chaotic. You have objects all around your dashboard canvas with different sizes. We will start the process of finishing our design.

 

Before proceeding, we save a copy of the dashboard.

Navigate to menu File ‘ Save As

 

Give a name to the file so that you can identify the raw dashboard definition file.

Click on Save.

Next, go to menu File => Close All

Note that there are no dashboards to view.

If you need more backup copies to be created or create different versions of the same dashboard definition, then go to the File Explorer, select the file and type – Ctrl-C, and then Ctrl-V

Now, Click on the File ‘ Open
Select the file “Order Management Analytics.icv”

Note that we are not touching the – Initial Copy file.
Click on Open

Get rid of objects you don’t need
We don’t need the initial table portlet, so we will delete that.

Select the “Name” portlet and then click on the “Scissor’ icon on the toolbar

 

Click “Yes” to confirm.

Note, we created the backup copy of the dashboard so don’t worry if you mess up the dashboard. You can always go back to the original and start again.

Similarly remove all objects that you don’t need it.

Next – Excel Dashboard Tutorial – Arrange objects in sizing and alignment