10 Data Problems Every Pipeline Hits (and the One-Liner Fixes)

The blog post titled "10 Data Problems Every Pipeline Hits (and How to Fix Them with GoldenFlow v1.1)" highlights common data quality issues encountered in data pipelines and introduces solutions using the GoldenFlow library, version 1.1. Below is a summary of the ten problems discussed along with their corresponding fixes:

Problem 1: Inconsistent Email Addresses

Issue: Emails are stored inconsistently (e.g., all lowercase, mixed case).

• Solution: Use email_standardize to convert emails to a consistent format.

Problem 2: Mixed Case URLs

Issue: URLs may be in different cases.

• Solution: Apply url_lowercase to ensure consistency.

Problem 3: Dashed and Spaced SSNs

Issue: Social Security Numbers (SSNs) are inconsistently formatted with dashes or spaces.

• Solution: Use ssn_format for normalization, and ssn_mask for masking sensitive information.

Problem 4: Inconsistent Country Names

Issue: Country names are entered in various languages, abbreviations, etc.

• Solution: Utilize country_standardize to map country names to ISO 3166-

Read the full article at DEV Community

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