What to do when you find data discrepancies?! I kinda felt like I did 6 loads of laundry, came out with socks I didn't even know I had, and then figured out how to match them up. Also, Spongebob, Rubix Cubes, and pivot tables.
Getting ready for your Q4 fundraising phone-a-thons? Follow these simple steps in Excel or Google Sheets to format your phone numbers for optimum ease!
Believe me, I have complete understanding for why you might not want to tackle that data junk drawer. That being said, I believe there are friendly, empowering, efficient ways to move through a data cleaning process. The first step is a mindset shift from thinking "we have already failed at this aahhhhhhh!" to "this is a normal, friendly, empowering way to take good care of our community!" Let's normalize data cleanup so we don't have to normalize data.
From a downloaded file with weird fonts and titles, wacky colors, no wrapped text, superwide columns, and repeating header rows, I was able to create a useable, sortable, shareable, printable, filterable, not-make-you-want-to-throw-your-computer-out-the-window spreadsheet. And you know what the best part is? You can too!
What do a camel, a mermaid, and an awesome job opportunity have in common? You'll have to read this post to find out, chock full of tips, gifs, puns and more!
In this installment of Dear Spreadsheet Whisperer, we hear from an old friend who's storing contact information in.... Quickbooks! I offer advice about how to make better use of contact segmentation features and how to begin to explore a better database system.
What does the moon, popcorn, and caterpillars have in common? Changing phases, of course! This post is all about getting better at change management. BONUS: my favorite lil dumpster fire meme makes a cameo appearance!
Inspired by Marie Kondo's new show about tidying your home, a post about keeping and deleting data in your spreadsheets and databases. With puns and gifs!
What is a mistake? Let's use the etymology to learn some lessons about mistakes and spreadsheets. Plus, puns and a recommendation for learning more.
On one hand, data skills are impossible to learn (and we blame the individual). On the other hand, companies tell us that advanced coding skills are easy to develop, 1, 2, 3! How can these be true at the same time? Who benefits from these messages? It's classic capitalism doublespeak: make non-data people feel insignificant and intimidated, then sell us a solution to our problem.
I call BULLSHIT on these dynamics and offer 8 tips for wrangling a sloppy spreadsheet that you can use right away!