Data quality KPIs critical in driving business success

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Data is gold in our increasingly digitised world, just as the value of gold is only realised in the refinement process. Data needs to be refined to unlock its real value. Unrefined data can damage businesses, their competitiveness and ability to capitalise on opportunities.

So, how do businesses end up with poor-quality data? Human error, outdated systems, inconsistent data-entry protocols and a lack of data governance lead to duplication, inaccuracies, inconsistencies and conflicting data sets. Without proper data governance there is no standardised process for maintaining high-quality data.

* Completeness ensures that all necessary data elements are present, which is essential for analysis and informed decision making. This involves mandatory fields in data entry systems, conducting audits to identify any gaps and automating the process of collecting relevant information. * Accuracy pertains to how the collected data mirrors reality. Implementing cross-checking mechanisms, using authoritative data sources, and regularly verifying data against external benchmarks are crucial for maintaining data accuracy.

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