After several years working with Microsoft Analysis Services, I decided to invest some time in learning more about Essbase. I have to say it has been a fascinating experience, both with regards to the platform’s endless possibilities and the quality of Oracle’s training program. I definitely should now update my post on Cubes & Universes;-)

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

• An awesome powertool buried in Excel
• How to use Microsoft Excel data tables to analyze information in a database
• How to create and use two-input data tables in Microsoft Excel

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;-)

The free Key Performance Indicator (KPI) Library is a community of business professionals that provides a catalogue of KPIs for identifying & prioritizing the KPIs that really matter for your organization’s success.

The library does get update quite regularly so far. Interesting stuff.

On-Line Analytical Processing (OLAP) is actually about business, it just sounds like a science project.

This potential confusion is one more hint that this field (multidimensional modeling and analysis but really Business Intelligence in general) requires both technical skills and business acumen. Probably just another argument in favor of Business Intelligence Competency Centers…

Still on the OLAP front, a new (beta) version of Palo is available. Wikipedia has a short summary:

Palo is a memory resident multidimensional (OLAP or MOLAP) database server [...] typically used as a Business Intelligence tool for Controlling and Budgeting purposes with Microsoft Excel as a user interface. Beyond the multidimensional data concept, Palo enables multiple users to share one centralised data storage (“Single version of the truth“).

There’s a (somewhat old) discussion thread here. I only played 10 minutes with it – it seems to offer many interesting features. You can also apparently connect Palo and Microsoft Analysis Services using software from Cubeware.

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.

• How do you know your spreadsheet is right?
• Spreadsheet Modelling Best Practice