Long time PHD reader and mother of a lovely kid, Michelle, sent me a question in email that provoked me to write this post,
I was wondering how to tabulate large amount of information gathered through surveys. Where I work customers are constantly handed survey sheets in order for us to measure how the service -among other things- is being perceived. Now, to put all that info into a spreadsheet (plus charts) can be really tedious.
So far I manage to get the job done by assigning 1 to 4 values were 1 sucks and 4 is great and so there I go column after column (each column is one individual survey) filling my 1 to 4’s answers. I know there’s an easy version with VBA; problem is that I am a total ignorant in that area. Any suggestions?
Few ideas that would make consolidation easy:
- Make sure all the source files are in the same format: make a template that your colleagues can use to input the data every month. This way you can use 3D references to summarize the data.
- Create a user form so that your audience can enter information in that instead of directly entering it in spreadsheet.
- Find out if the survey or other type data collection can be fed to a database. This way, every month we can import the data using data connections.
- If we actually end up with sheets with different data formats, spend sometime and study the anomalies. Then you can develop a small macro or find-replace routine that would clean the data. [related: clean data using excel]
- Try to save the files as CSV and open them in a regular expression capable editor like Notepad++. Now match and clean up data.
- All else fails, get a strong cup of coffee, put on some music, roll your sleeves and start alt+tabbing.
But more than these ideas, I am interested to know how YOU solve this problem.
I think this is a very common problem. Since I have very little experience in the area of consolidating data from multiple sheets in to one, I couldn’t give her any real advise. So now I am turning to you.
- Do you use any add-ins or macros to consolidate data? What is your experience like, what would you recommend?
- What shortcuts, ideas and cool things you use when working on data from multiple sheets?
- How do you usually clean / normalize the data?
Please discuss.
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.