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The Hidden Work Behind Great Results: What Repainting a Window Trim Taught Me About Data Analytics

Over the past two days, I took on the task of repainting the wooden window trim of my parents’ house. These windows hadn’t been well maintained for over 35 years, so what should have been a straightforward painting job turned into something much more labor-intensive. While the job is called “painting,” I quickly realized that painting itself accounted for only about 20-30% of the effort. The real work was in the preparation—sanding the windows, patching holes, taping up the glass, and then cleaning up afterward. And just as importantly, the final cleaning and presentation of the finished work made the difference in how it was received—ensuring that no defects stood out to be nitpicked.

This experience got me thinking: isn’t this exactly like data analytics?

The Focus on the Final Product

When people think about data analytics, they often picture beautiful dashboards, interactive charts, and compelling insights that drive action. These elements are the “paint” of data analytics—the part that gets noticed and appreciated. But just like in painting, where a smooth and durable finish depends on the quality of preparation, the effectiveness of any data analytics project relies on the foundational work that happens long before the final visualizations are created.

The Dirty, Unseen Work

In painting, preparation takes the majority of the time. Without proper sanding, old paint and grime create an uneven surface, making the new coat look bad and peel quickly. Without filling in holes and cracks, imperfections become visible, reducing the overall quality of the finish. Without taping up the glass, paint bleeds into unwanted areas, creating a messy and unprofessional look.

Similarly, in data analytics, much of the effort is spent preparing the data before it can be used effectively:

Data Cleaning – Removing duplicates, correcting errors, and standardizing formats (like sanding off the old paint and grime).
Data Structuring – Organizing raw data into usable formats, defining categories, and ensuring consistency (like patching up holes and cracks).
Data Validation – Checking for missing or inconsistent values and ensuring data quality (like making sure the surface is smooth before painting).
Data Integration – Merging multiple data sources and ensuring compatibility (like making sure all trim pieces fit together seamlessly).

These steps aren’t glamorous. In fact, they’re tedious, time-consuming, and often frustrating. But skipping them leads to unreliable, misleading, or outright incorrect analyses—just as a rushed paint job would result in a shabby, peeling window trim within months.

The Payoff: A Smooth Finish and Reliable Insights

Once all the prep work is done in painting, the actual painting process is straightforward and rewarding. The brush glides smoothly, the paint adheres well, and the final result is durable and visually appealing. Additionally, the final clean-up and presentation ensure that the work is well received and any flaws remain unnoticed.

Likewise, when the groundwork in data analytics is done properly, analysis becomes much easier and far more valuable. Insights are accurate, dashboards are meaningful, and decision-makers can trust the data. The best analysts know that the secret to compelling analytics isn’t just in the visualization—it’s in the preparation and in presenting the results in a way that leaves no room for doubt or nitpicking.

Final Thoughts

Repainting the window trim was a stark reminder that behind every polished end product—whether it’s a freshly painted house or a well-executed data report—there’s a significant amount of unseen, unglamorous effort. The next time you see a stunning data visualization, remember the countless hours spent cleaning, structuring, and validating the data behind it. The real work often isn’t in what’s visible; it’s in the foundation that makes everything else possible. And just like with painting, if you want to do it right, you can’t skip the prep work—or the final polish.

If you or your organization are looking to build practical data analytics capabilities and develop the skills needed to turn raw data into meaningful insights, reach out to FYT Consulting. We specialize in making data analytics approachable and actionable, helping professionals and enterprises harness the power of data to drive real impact. Contact us today to learn how we can help!