Can you imagine building a complex worksheet without formulas? I can’t. While no one can dispute the usability of formulas, we all know how painful it is when an excel formula returns a mysterious error and we don’t know what is causing it.
When I learned IF() formula for the first time, I have spent a whole Sunday morning debugging a stupid error in a grade calculation formula.
So as part of our spreadcheats series, we will learn a handy trick you can use to debug formulas and fix the errors quickly.
Assuming we have a moderately lengthy formula like this
=IF(AVERAGE(B2:B6)<=AVERAGE(C2:C6),MAX(B2:B6),MAX(C2:C6))
and we want to know where the error is occurring
- Select the cell with formula.
- Now click on the formula bar
- Just select the parts the formula and press F9 (for eg: the first average() formula)
- This will evaluate only the selected part and replaces it with the result. Like this:
- Using this technique you can narrow down the errors to particular range or values causing it.
- Now that you know where the error is occurring you can wrap that part of formula with an ISERROR() formula to avoid unpleasant surprises.
What is your favorite way of handling errors?
PS: If you have mailed me or commented here and waiting for a response, please give me some more time. I am having trouble getting internet connection in Chennai and visiting browsing center to respond to mails is not a pleasant experience either. I really appreciate your patience. Meanwhile if you know any free wi-fi hot spots in Chennai do let me know through comments. 🙂
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.