4 High Impact Data Quality Issues That Are Easily Avoidable

No-brainer guardrails you should always set up for your data operations

Photo by Hogarth de la Plante on Unsplash

When we talk to prospective customers, their first questions are usually around the fundamentals of data quality, including what it is, how we measure it, what happens when it goes south, and how issues can be prevented.

Our answers always come back to the core that drives our mission: data is the lifeblood of the modern enterprise, and having the confidence to make business decisions based on data is critical. Data quality, then, is the quality of that lifeblood. In order for it to power your business engine correctly, it’s important to continuously perform accurate and comprehensive data quality checks. It’s also important to focus these checks on data that has the potential to have the highest impact on business decision-making — especially when you’re trying to monitor data quality at scale.

What’s hard about monitoring data quality at scale?