Hello readers, I have an exciting announcement for you.
I will be presenting at two events at London in April 2020. Please consider this my personal invitation and join me for Excel + Power BI fun.
01 – Global Excel Summit 2020
London, 21-22 April 2020 (Tuesday & Wednesday)
I am thrilled and honored to be presenting at Global Excel Summit in London, coming April. I will be doing a full day session on advanced charting and one hour presentation on how I built a million dollar product running my online business.
You will be hearing from Excel / Power BI greats such as Bob Umlas, Boriana Petrova, Gasper Kamensek, Oz Du Soleil, Sumit Bansal, Leila Gharani and many others.
This is a must attend event if you live close by or need an excuse to visit London.
10% discount for Chandoo.org readers
Please use the promo code Chandoo-10% to get 10% discount on the global summit ticket price.
Click here to know more and book your spot.
02 – Excel + Power BI Masterclass
London – 23,24 April 2020 (Thursday & Friday)
If a large conference is not for you or you just can’t get enough of that Excel + Power BI goodness, then please consider my special Masterclass event. In this two event, you will learn,
- Day 1 – Advanced Dashboard Reporting with Excel
- Day 2 – Mastering Power BI, Power Query and Power Pivot
Each day is a standalone course, so you can sign up for either of them or both.
Early bird discount – sign up before end of year
If you sign up before end of this year (2019), you will get £50 off one day option or £75 off two day option.
Thank you and see you in London 🙂
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.