You may remember the day you were introduced to Excel’s pivot tables. It might have happened through a co-worker, a book or an online tutorial but the effect was probably along the lines of: “Wow! How did I ever analyze data without them?”
Well, I sort of went through the same experience again several months ago reading about Dermot Balson’s Merge pattern (sample file here) – thanks to a post by Jim Johnson. I would love to elaborate some other time on Dermot’s idea of applying the concept of design pattern to spreadsheets but I will delve here specifically into his merge pattern, which makes use of Excel data tables.
According to Microsoft, data tables allow you to “test different input values for a formula without having to retype or copy the formula for each value” (Q282852). This is typically useful for sensitivity analysis, but it also works great for running complex calculations against multiple records in a data set.
I’ve argued before that most (structured) data benefits from being stored in a a flat file format. One of the downsides of doing so, however, is the amount of work involved in running a complex Excel model against all rows in a flat file. If you don’t intend to migrate your model to a relational or multidimensional database, then data tables as a wonderful way of achieving just that – free-form spreadsheet computations applied to structured data.
Additional links of interest
Happy Excel modeling!
You’ve probably noticed that you shouldn’t trust this blog for real-time news tracking. The following are essentially timeless, however, so here we go…
Rob van Gelder (of DailyDoseOfExcel fame) shared a tip back in May on how to build a simple Gantt chart in Excel. I’m posting a link here because it’s the easiest I’ve seen so far.
Jeff Smith exposes his Golden Rule of data Manipulation over at sqlteam.com. While he elaborates on his statement from a programmer’s standpoint, it’s all applicable to knowledge workers and spreadsheets:
“It is always easier and more flexible to combine data elements rather than to break them apart”
From a data analysis standpoint, Jeff’s examples are essentially related to what I would call attributes (such as phone numbers). His rule still holds true with values, though. As you work towards summarizing a data set (say, daily financial transactions that you want to analyze by month), you’ll want to aggregate values as late as possible instead of running the risk of losing valuable information by aggregating too early. Spreadsheet programs hit a limit between 65k and 1M records, but there are tools to take it from there – which brings us to Paul Steynberg’s advice for considering OLAP tools as part of a financial system manager’s toolbox.
OLAP technologies are particularly well suited to handling large amounts of data. I personally share Paul’s opinion of Microsoft’s SQL Server Analysis Services, which I would describe to the non-initiated as Excel on steroids. On lots of steroids, that is. SSAS gives you access to summaries and advanced computations based on millions of underlying records, usually responding in just a few seconds.
EDIT (Sep. 10, 2008): Using a definition as crude as “Excel on steroids” for SSAS left me feeling a little guilty. I’m over it now, having just read Andrew Fryer’s post on business intelligence for small business;-)
Andreas Lipphardt informed me that BonaVista Systems (or should we now say XLCubed?) are running an Excel dashboard competition. Participants can win an iPhone, a data visualization workshop or one of Stephen Few’s books.
Now this is interesting. Not only do the XLCubed and MicroCharts Excel add-ins work much better together today than when I originally wrote about combining them, but the publisher of the former has actually acquired the publisher of the latter. This is extracted from the message that went out to MicroCharts users:
Linking XLCubed with MicroCharts connects Dashboards direct to the data and makes them dynamic. It also makes them easier to build as the OLAP Cube can also store the control information for the dashboard as well as the data.
This sounds promising, particularly if microcharts are made available within XLCbubed grids. Formula-mode integration is perfect for dashboard-style reporting but remains limited for dynamically exploring data. More on all this when I’ve had a chance to actually try the “integrated” version.
Thanks to Dick Kusleika‘s article on EuSpRIG 2007 and after browsing the latter site a bit, I located a couple interesting papers I want to share here. These are full of good high-level tips related to spreadshet design:
I just happened to discover the Accounting Mechanics blog which focuses on “tools and techniques of the management accountant” and happens to have a link back to my own blog. I’ll catch up with posts there as soon as possible since there seems to be quite a few interesting articles. I’ve already spotted the following:
There’s also a link to another potentially interesting blog, that one focusing on “professional spreadsheet development stuff”.
Charles W. Kyd has posted several great articles on his ExcelUser website:
If you spend your days working with Excel, you’ll want to subscribe to Charles’ Excel for Business newsletter.