Every week, this blog features 5 of the best visualizations from the last week around the web.
Average gas prices in US regions from 1993 plotted in dynamic bar
Flowing data takes a look at the historical gasoline price data and provides us this eye candy.
My friend Jon takes a look at this and recreates it in excel. Read more.[via flowingdata]
Cost of Food around the World
This BBC page provides insights in to changing food price, consumption trends around the world. Scary picture for future generations. [via cool infographics]
Infographic on the Tees, the shirt project
With so many beautiful visualizations, the shirt project is the next natural thing to happen. They spread the story from the charts in a fun way. Go buy one if you like it 🙂
Google Search Insights for search term “excel”
Google has launched search insights which provides excellent detail about various search trends. I have looked up search term excel, and surprisingly India leads the pack with index of 100. Now I know where majority of my audience are 🙂
How the marginal taxes are changing with Obama’s new tax policy
This chart explains how the marginal taxes change with proposed tax structure by Barack Obama. Remember, the key word is marginal (loosely put, since Obama’s tax policies put more money in your pocket, your other taxes will go up) [via marginal revolution]
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.