10 Quick Wins with Data You Can Tackle Today

When you’re working with data, it’s easy to fall into “wait and see” mode. Waiting for that perfect dashboard. Waiting for tools to be implemented. Waiting for someone to sign off on a bigger project. 

But you don’t have to wait to get value out of your data. 

These 10 quick wins take five to 10 minutes each and can make a real difference in how clean, usable, and AI-ready your data is—without waiting on a workflow redesign or new tech stack. Whether you’re deep in spreadsheets, building dashboards, or wrangling pipelines, there’s something here to help make your day easier and your data better. 

But, maybe you’re ready to make even bigger moves with your data. Request a custom consultation to explore ways that we at Domo can help you build on these quick wins—with no overhaul required.

1. Check your date formats 

Start simple. If you’ve ever built a report and ended up with mismatched weeks or misaligned time series, inconsistent date formats were probably to blame. Run a quick scan: Are all your dates in the same format? Watch out for rogue timestamps or month/day flips. 

2. Clean up your geo abbreviations 

State and airport codes are often inconsistent, especially when pulled from different sources. Take five minutes to scan for weird or unusual spellings, three-letter vs. two-letter codes, or alternate naming conventions. Small fix, big ripple effect. 

3. Review Boolean fields for null values 

If you see a column with values like “true,” “false,” and then a bunch of blanks or nulls, it’s a red flag. Those empty cells may seem harmless, but they can quietly break filters and logic operations. It’s a quick check—one that pays off in fewer downstream issues. 

4. Verify one-to-one ID-to-description relationships 

A classic catch: Maybe you want campaign ID 123 to always mean “Spring Sale,” but sometimes it doesn’t. Especially in marketing data sets, reused names or IDs can create hidden inconsistencies. Spot them early, and you’ll save yourself and your team from confusion later. 

5. Alias column names to business-friendly terms 

If your field is named cust_id_hash_c_01, stop right now. Rename or alias it to something your coworkers—and AI tools—can actually understand. This small step makes your data more readable and makes downstream metadata cleaner, too. 

6. Use a prebuilt date spine to simplify time fields 

Transforming dates into weeks, months, or quarters can get messy fast. You can avoid it by downloading a standard date spine data set and joining it to your data. Now you have a shortcut that saves you hours of formatting work down the line. 

7. Standardize geo data with off-the-shelf references 

You don’t have to manually fix every “CA” versus “California” inconsistency. Many tools offer ready-made geo data sets that handle state names, zip codes, and abbreviations for you. Use one and skip the tedium. 

8. Build an Excel template for recurring reports 

If you’re still copying and pasting data into a spreadsheet each week, take 10 minutes to set up a template in your favorite spreadsheet program. Keep raw data in one tab, formulas and visualizations in another. Then just drop in new data and watch your charts update. 

9. Keep raw data separate from reports 

This applies across tools—Excel, Domo, you name it. Don’t clutter your reporting tab with source data. Keeping raw data separate from your calculations prevents accidental changes, reduces bugs, and makes reuse easier. 

10. Use connectors (or reverse ETL) to skip manual uploads 

Sending lists from one system to another? Don’t. Avoid manual transfers and use tools like Domo to push data between platforms automatically. One example: Instead of uploading prospect lists to Salesforce manually, use a connector to sync it directly. It’s faster, cleaner, and saves hours every week. 

One last thing: AI is only as good as your data 

Metadata might sound like a backend concern, but it’s actually one of the best ways to prepare your data for AI tools. Describing your data fields in plain language—either through aliases or column notes—helps both humans and machines understand what the data means. Whether you’re using Domo.AI, DomoGPT, or another generative AI tool, the more context you give, the better the output. 

And when it comes to AI-assisted coding? Tools like ChatGPT can be surprisingly helpful for writing SQL or Python functions and handling common debugging issues. While coding forums like Stack Overflow aren’t going away, many analysts are turning to large language models (LLMs) first because they offer faster and more tailored responses to your specific question. 

Keep the momentum going 

Start with these small victories, and you’ll not only save time—you’ll set yourself up for faster, smarter, and cleaner work in every part of your data pipeline.

But they’re just the beginning. If you want more, request a custom consultation to find out how Domo can help you automate the busywork, scale your insights, and set up smarter, AI-ready workflows—without a massive overhaul.

Let’s build on what you’ve already started.