This is a Guest Post by Robert on Visualization Techniques for KPI Dashboards using Excel.
This 6 Part Tutorial on Management Dashboards Teaches YOU:
Creating a Scrollable List View in Dashboard
Add Ability to Sort on Any KPI to the Dashboard
Highlight KPIs Based on Percentile
Add Microcharts to KPI Dashboards
Compare 2 KPIs in the Dashboards Using Form Controls
Show the Distribution of a KPI using Box Plots
As you all know dashboards provide “Information at a glance” with often the power to “deep dive to analyze”. Most dashboards succeed in providing information. But the exceptional ones succeed in “at a glance” part of it while maintaining the deep diving capabilities. In this and next post we will discuss 2 powerful visualizations that can be added to your dashboards to provide better insights at a glance. If you are not familiar with excel based dashboards we recommend reading the dashboards using excel.
The challenge
Part 3 of the series already displays parts of the relationships within the 5 KPI data sets by highlighting the 10% best and 10% poorest performers of the 4 KPI that are not selected as the sort criteria. But what if we want to have a closer look on how the KPI are related to each other? We need another analytical feature that enables the user to compare the complete data sets at a glance in a graphical visualization.
The solution
An XY scatter chart is the best way to analyze and visualize the relationship and correlation between two sets of quantitative data.
An XY scatter chart, however, is 2-dimensional and therefore limited to compare only two data sets.
Since we have 5 different KPI, we would need 10 different charts to display all possible combinations of KPI pairs on our dashboard. This would need too much real estate on the dashboard and it would probably be too complex and unclear for the users of the dashboard.
Again we need an interactive, flexible way to display the data in one single chart and let the user decide which 2 KPI to display (see above). Additionally we want to highlight the data points that are displayed on the dashboard table and of course we want to do this without VBA.
The implementation
Download Excel Dashboard Visualization Techniques [part 1] workbook and read on how this is implemented.
- Create an input list form control with the names of the 5 KPI (calculation!E10:E14)
- Define two cells to store the results of the combo boxes to select the displayed KPI (calculation!E16:E17)
- Insert two combo boxes (from the forms control toolbar) on the dashboard and link the input lists and the cell links accordingly.
Add 4 extra columns (calculation!AS:AT and calculation!AV:AW) and create OFFSET formulas to fill these new cell ranges with the values of the selected KPI (i.e. using the values in calculation!E16:E17, see 2.).- Create an XY scatter chart with two data series (data source: the 4 new cell ranges, see 4.). Format the first series as circles without fill colors and the second series as circles with a grey fill color, add a legend to the chart and bring the chart to the dashboard.
- Reposition the chart on the dashboard (remember this trick: keeping the ALT-key pressed during resizing and repositioning makes the chart auto-fit to the cell grid underneath) and position the combo boxes.
- If you want to, you could easily add a trend line to the chart and display the equation and/or the R-squared value for deeper analysis of the correlation between the two KPIs.
That’s it. Play around with the new analytical feature: change the selected two KPIs, change the sort criteria, toggle the sort order or scroll up and down the dashboard table and watch the changes on the XY scatter chart.
What’s next? – Last Part of the KPI Dashboards using Excel
Make sure you have downloaded the Excel Dashboard Visualization Techniques [part 1] workbook
Go to next post: Part 6: Show the Distribution of a KPI using Box Plots
Also, Checkout our Excel Dashboards Page for more examples and resources.
Chandoo’s note: Thanks Robert for another excellent post.
Please leave your comments, questions and love here, Robert is a regular reader of this blog he will be happy to respond to you as early as possible.
One Response to “SQL vs. Power Query – The Ultimate Comparison”
Enjoyed your SQL / Power Query podcast (A LOT). I've used SQL a little longer than Chandoo. Power Query not so much.
Today I still use SQL & VBA for my "go to" applications. While I don't pull billions of rows, I do pull millions. I agree with Chandoo about Power Query (PQ) lack of performance. I've tried to benchmark PQ to SQL and I find that a well written SQL will work much faster. Like mentioned in the podcast, my similar conclusion is that SQL is doing the filtering on the server while PQ is pulling data into the local computer and then filtering the data. I've heard about PQ query folding but I still prefer SQL.
My typical excel application will use SQL to pull data from an Enterprise DB. I load data into Structured Tables and/or Excel Power Pivot (especially if there's lot of data).
I like to have a Control Worksheet to enter parameters, display error messages and have user buttons to execute VBA. I use VBA to build/edit parameters used in the SQL. Sometimes I use parameter-based SQL. Sometimes I create a custom SQL String in a hidden worksheet that I then pull into VBA code (these may build a string of comma separated values that's used with a SQL include). Another SQL trick I like to do is tag my data with a YY-MM, YY-QTR, or YY-Week field constructed form a Transaction Date.
In an application, I like to create a dashboard(s) that may contain hyperlinks that allow the end-user to drill into data. Sometimes the hyperlink will point to worksheet and sometimes to a supporting workbook. In some cases, I use a double click VBA Macro that will pull additional data and direct the user to a supplemental worksheet or pivot table.
In recent years I like Dynamic Formulas & Lambda Functions. I find this preferable to pivot tales and slicers. I like to use a Lambda in conjunction with a cube formula to pull data from a power pivot data model. I.E. a Lambda using a cube formula to aggregate Accounting Data by a general ledger account and financial period. Rather than present info in a power pivot table, you can use this combination to easily build financial reports in a format that's familiar to Accounting Professionals.
One thing that PQ does very well is consolidating data from separate files. In the old days this was always a pain.
I've found that using SQL can be very trying (even for someone with experience). It's largely an iterative process. Start simple then use Xlookup (old days Match/Index). Once you get the relationships correct you can then use SQL joins to construct a well behaved SQL statement.
Most professional enterprise systems offer a schema that's very valuable for constructing SQL statements. For any given enterprise system there's often a community of users that will share SQL. I.E. MS Great Plains was a great source (but I haven't used them in years).
Hope this long reply has value - keep up the good work.