Today, I want to introduce an excel hero to you. He may not be wearing red cape or carrying latest ninja weaponry with him. But he is a hero. He can arm twist toughest sets of data to create beautiful (almost art like) charts or animations. He can a complex vba model and make it look lean, mean and clean.
Today, I want to introduce Daniel Ferry to you. I have been reading Daniel’s Excel Hero blog for the last few months. He writes a lot about advanced charting & vba and uses the blog to showcase how he plays with excel. The blog is true to its name and displays some of the most sophisticated excel trickery I have ever seen.
Here are a few examples of his outstanding work:
- An Excel Chess Game Viewer: In this beautiful animated chart, Daniel visualizes one of the popular chess games.
- NFL Drive Chart: A colorful animated chart showing an NFL game, step by step.
- Multi-threaded VBA: Discussion on techniques and approach to creating multiple threads thru VBA.
- Understanding Excel’s IF formula: an indepth view of excel’s if formula and faster alternatives to it.
- Celtic Muse: a fantastic animated chart showing Celtic muse art form in 78000 tiles… 😮
If you are an Excel enthusiast or hobby programmer, I recommend following Daniel’s blog (rss here) to get fresh ideas, inspiration and source workbooks on regular basis.
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.