From the course: Data Quality Testing with Great Expectations
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Why data quality matters - Great Expectations Tutorial
From the course: Data Quality Testing with Great Expectations
Why data quality matters
Every dashboard, AI model, and business decision is only as good as the data that powers it. Today, data is at the center of nearly every business function. It's used to track business performance, forecast demand, and power automated decision-making. But this only works if the underlying data can be trusted. When data is incomplete, inaccurate, or inconsistent, it leads to flawed insights, wasted time, and costly decisions. For example, imagine a marketing team that uses website analytics to measure how many site visitors convert into actual customers. One day, a track intact breaks on the website and stops recording some of those conversions. The marketing dashboard still showed data and nothing looks obviously wrong, but the numbers are now incomplete. Over time, the team believes that the conversion rate has dropped and starts changing the strategy or even cutting the budget. The problem here isn't a dramatic error, but missing data that sneakily impacts decision making. Data…
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