🎓 Step 1: I Got Certified!
✍🏻 Step 2: Demonstrating my understanding of data cleaning!
Imagine you’re baking cookies for a bake sale. You have all your ingredients laid out: flour, sugar, eggs, and chocolate chips. But as you start mixing, you realize your sugar is mixed with salt, the flour has lumps, and some eggs are cracked. You end up with a batch of cookies that taste terrible, and no one wants to buy them.
This is what happens when your dataset isn’t clean before analysis, it’s like trying to bake with bad ingredients. If you take the time to sift the flour, check the sugar, and pick the freshest eggs, you’ll end up with delicious cookies that everyone loves.
Enough cookies for now, let’s talk data! In data analysis, this process of preparing your "ingredients" is called data cleaning. It ensures your data is accurate and consistent, so your results are trustworthy. Without it, your insights could be as unreliable as those salty cookies, leading to poor decisions.
Common data issues include missing values (e.g., nulls, blanks, or empty spaces) and invalid values like typos (“Burgre” instead of “Burger”) or out-of-range entries (e.g., negative ages). Inconsistent data formats can also cause trouble, such as mixed date formats (YYYY-MM-DD vs. DD/MM/YYYY) or inconsistent capitalizations (“Paris” vs. “PARIS”). Even abbreviations like "U.S." versus "USA" need standardization. Other problems include wrong data types (e.g., "$15" in a numeric column), duplicate entries, and incorrect calculations where derived values don’t match their components. These errors, if left unaddressed, can lead to misleading insights and poor decision-making.
As data analysts, we dig into the data to spot and fix data issues, clean up inconsistencies, and sometimes, we just have to filter out or exclude the stuff we can’t fix from the analysis. That’s data cleaning in a nutshell.
🖼️ Step 3: Visual Guide
Attribution: All icons and images used in the designs above are from freepik.com
🙋🏻♂️ Step 4: Wrapping Up with Buzz & Woody
Meme source imgflip.com
I hope you enjoyed the tour in my data-kitchen, prepared for your enjoyment in mind.
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