Effectively managing data requires identifying and resolving common data quality issues. Discover strategies for overcoming these challenges

Last week, Sky News published a story on how a series of Excel issues and errors caused the loss of over 16000 positive COVID-19 cases – delaying tracing, in some cases for as long as a week.

By the time this error was detected and corrected thousands of people may have been exposed to these missing positives – literally a life-and-death error.

This story highlights the reality that Excel, which remains a widely popular tool for reporting and analysis, is prone to this kind of difficult-to-detect error.

Improving data quality in Excel

Of course, one can take some steps to improve data quality in Excel – although the inherent issues mean that this may never be 100%.

One can also leverage solutions like MANTA to track lineage and transformation through Excel. This will help to ensure an understanding of where Excel report data is coming from and how it flows through Excel.

In practice, while Excel remains a fantastic tool for ad hoc analysis, for serious production analytics it must surely be time to give up on Excel.

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