Even the most powerful analytical tools are only as good as the data they crunch, and intelligence built on bad data can be worse than no analysis at all. Far too often, companies make large decisions or formulate strategic objectives with full knowledge – or at least a strong inkling – that their data is flawed or incomplete, simply because they can’t see past the status quo.

What can businesses do to avoid making tragic business decisions or exposing the organization to increased risks? Implementing both data quality and governance measures are the key to getting data back on track, yet the idea of analyzing and scrubbing data is well-trodden ground for business intelligence managers. Rarely do BI executives discuss actionable steps about how to prevent poor data from entering the system in the first place. While it may be an old topic, few do it well.

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