Situation
We know that VLOOKUP formula is useful to fetch the first matching item from a list. So what would you do if you need 2nd (or 3rd etc.) matching item from a list?
For eg. If you have below data, and you want to find out how much sales John made 2nd time, then VLOOKUP formula becomes quite useless. Or is it?!?
Data:
Solution
A simple solution to this problem would be sorting our data on sales person’s name. That way all Johns would line up one beneath another. And we just have to find the first John’s position and add 1 to it to get to 2nd occurrence. Like this =MATCH("John", C5:C17, 0) + 1
But sorting is not an option all the time. So there should be a better way to do this?
Well, there is. We just add a helper column before the sales person name and fill it with sales-person’s name & occurrence. (see the below data table).
For this we can use COUNTIF() Formula, like this: =C5&COUNTIF($C$5:C5,C5). Notice the $C$5:C5?, well the mix of absolute & relative references does the trick here and gets John1, John2… etc.
Now, to lookup 2nd occurance of John, all we do is, simply write =VLOOKUP("John2",...) and we are done.
Sample File
Download Example File – Getting the 2nd matching item from a list using VLOOKUP formula
The file includes few examples on how to fetch 2nd, 3rd etc. matches using lookup formulas. It also has some interesting (and challenging) home work for you. Download & play with it.
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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.