Without a proper data foundation, even the most advanced AI tools will fail to deliver consistent, predictable results, writes Dun & Bradstreet’s David Marshall.

It has been estimated by MITSloan that the cumulative cost of inaccurate data is 15 to 25 per cent of revenue for most organisations. This is because poor quality data wastes resources, undermines ...

Marketers suffer from a variety of negative consequences stemming from poor-quality data that collectively drains marketing resources and limits effectiveness. Wasted media spend is the most ...

In today’s fast-evolving world of AI, the importance of data quality cannot be overstated. As AI systems rely heavily on data for training, validation, and testing, the old saying “garbage in, garbage ...

Challenges with data quality and data governance have plagued healthcare analytics efforts for decades – and the stakes are only getting higher in the age of AI. Inaccurate or inconsistent data ...

More than three-quarters of business leaders say they’re under growing pressure to drive business value with data, according to a Salesforce report, but many leaders say their data is often outdated, ...

For all the talk of innovation and analytics, most business decisions still come down to trust. Can we trust what the numbers are telling us? Can we trust that our systems are secure? Can we trust the ...

It’s no surprise to anyone who works with data—it’s messy. In every industry and every business, there are data anomalies and issues that can impact the story data tells. If we have any hope of ...

Everyone understands data is important, but many business leaders don’t realize how impactful data quality can be on day-to-day operations. In my experience, nearly all process breakdowns have root ...