We know that using VLOOKUP, we can find a value corresponding to a given item. For example Sales of x. But what if you have multiple sales for each item and you want the last value?
Today lets understand how to find the last date of an activity, given data like this:
[Note: thanks to SDK who asked this question in a comment]
Like everything else in Excel, there are multiple ways to finding last date. If cats can use computers, they would hate Excel. You see, Excel is overflowing with unlimited ways to skin a cat.
Method 1: Using LOOKUP formula
Assuming the data is in range,
- Dates in $C$3:$F$3
- x marks in C4:F4
We can use =LOOKUP(“y”, C4:F4, $C$3:$F$3) to find the last date.
Why find y? Simple, since our data has “x” against date & name combinations, we just find the next letter (y). So LOOKUP formula stops looking after finding the last x. You see, LOOKUP formula assumes the list is sorted, so if it cannot find a match (in our case – y), it would return the closest match (ie, the last x).
Related: Comprehensive guide to Excel VLOOKUP & other LOOKUP formulas.
Method 2: Using MAX & SUMPRODUCT
I am like Gus Portokalos in My Big Fat Greek Wedding movie. SUMPRODUCT is my Windex. I use it for tough data, complex questions, sores, minor ailments & occasional car dents.
In this case, a formula like =SUMPRODUCT(MAX(($C$3:$F$3)*(C4:F4=”x”))) would do the job.
To be honest, just MAX(($C$3:$F$3)*(C4:F4=”x”)) would do too, but then you have to CTRL+Shift+Enter it.
How does it work? Since dates are just numbers, we take the dates & multiply them wherever there is x. So, it would be,
{41091,41092,41093,41094}*{TRUE,TRUE,FALSE,FALSE}
Which will be,
{41091,41092,0,0}
Then we find the maximum of this, which is 41092 (the number corresponding to 2-jul-2012).
Since this is an array operation, we can either CTRL+Shift+Enter it or wrap it inside SUMPRODUCT, like the G(r)eeks do. And that gives the answer.
More on this: Writing MAXIF formula in Excel, Introduction to SUMPRODUCT
Download Example Workbook
Click here to download example workbook. I have a bonus homework form you in there. Go ahead and solve it.
Your Homework
Time for a quiz. How would you find last date for a given name, if your data is like this?
Go ahead and share your answer.
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.