October has been another fantastic month since I stared this blog. We had 100k page views, the RSS subscriber count nearly touched 1500. There were 33 posts and 280 comments (WOW). Even our Facebook fan club reached the milestone of 10 members. For a loooong time myself and a friend whom I persuaded to join it were the only members there. So, thanks everyone for your love and support.
You all have been a constant motivation for me to learn & share new things about excel (which is also making me uber productive at work btw. The other day, my boss nearly fainted when I solved something in minutes. So thank you all 🙂 )
Here is a list 10 best posts (full archive for Oct 08):
- Simple Todo List App using Excel [01 October]
- Download and play Deal or No Deal in Excel [03 October]
- Radar Chart Alternatives – Spot Matrix Charts [07 October]
- 35 Cool Visualizations on 2008 US Presidential Election [07 October]
- Excel Dashboard Visualization Tips – Part 1, Part 2 [09 October]
- VBA Macro to get more than 3 Conditional Formats in Excel [14 October]
- 15 MS Excel Tips to Make you a Productivity Guru [16 October]
- Reader Poll: Should the axis for bar charts always start at zero? [21 October]
- Sorting Text in Excel using Formulas [22 October]
- 5 Chart Formatting Tips [28 October]
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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.