Apply Data Cleaning Basics
Skills:
Data Literacy80%
Key Takeaways
Applies data cleaning basics to marketing datasets using normalization and standardization techniques
Original Description
Messy marketing data leads to inaccurate reporting, wasted budget, and poor business decisions. In this course, you’ll learn how to clean and validate marketing datasets so you can trust the numbers behind your campaigns.
You’ll begin with the fundamentals of marketing data cleaning, including how to normalize UTM parameters, standardize inconsistent channel names, remove duplicate records, and fix whitespace and formatting issues that distort reporting. Using spreadsheet tools and basic SQL concepts, you’ll apply practical cleaning routines to realistic multi channel marketing datasets.
Next, you’ll learn how to validate and reconcile conversion counts across platforms like GA4, Facebook Ads, and Salesforce CRM. You’ll explore why conversion numbers differ between systems and build validation workflows that identify discrepancies, calculate variance percentages, and establish a reliable source of truth for reporting.
Through hands on labs and realistic scenarios from a fictional e-commerce brand, you’ll clean campaign datasets, build validation scripts, and investigate conversion discrepancies caused by attribution windows, tracking behavior, and duplicate events.
By the end of the course, you’ll be able to prepare cleaner datasets for analysis, identify common marketing data quality issues, and validate reporting accuracy across platforms with confidence.
This course is ideal for junior marketing analysts, digital marketers, and business professionals responsible for campaign reporting or marketing analytics.
Watch on External: Coursera ↗
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