Poor data quality undermines good decision-making and dooms many AI initiatives. However, many organizations are operating in unmanaged data mode or organized cleanup mode, with low-quality data. Companies that make the move to proactive prevention mode, in which data errors are prevented at the source, benefit from better business decisions and more trustworthy analytics. Learn how to help your organization make the leap, as executives at meal-kit company HelloFresh did. When it comes to dealing with data quality, teams and companies fall into one of three modes: unmanaged, organized cleanup, or proactive prevention. Most organizations get stuck in one of the first two. The work of addressing data issues is demanding, messy, and time-consuming. Poor-quality data can cripple decision-making and doom generative AI projects, since bad data fed to AI models turns into untrustworthy results. The real data quality breakthrough happens when companies transition to the third mode, where...
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