‘Dirty data’ poses risk to quality analytics

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More than half of firms surveyed kept their data at on-premise servers.
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Businesses are being warned “dirty data” poses a risk as they work on implementing artificial intelligence-powered tools.

Research by technology company Datacom showed just 9 percent of New Zealand businesses considered all of their data to be “clean” and 30 percent felt that figure was half or less.

Dirty data was data that contained duplicates, or was outdated, insecure, incomplete, inaccurate or inconsistent.

The findings were based on a survey of 200 senior data and IT managers in the country.

Datacom New Zealand managing director Justin Gray said dirty data presented significant risks for businesses as AI usage increased.

“The quality of AI outputs is wholly dependent on the quality of data that is available – garbage in, garbage out.

“For example, AI can be a powerful predictive tool and can identify patterns and trends within your business that you can use to guide strategic decisions, but if the data is off, then the AI analytics will be too.”

Businesses lacked adequate practices around data management, Gray said, with the survey showing 40 percent of firms did not conduct regular data cleansing.

“The results show a clear need for data and IT managers to re-evaluate their current processes if they want to use their data as the foundation for quality real-time analytics and insights, and if they plan to introduce AI tools and platforms into their business that will rely on the integrity and accuracy of their data,” he said.

The research also found more than half of firms kept their data at on-premise servers, with about 31 to 35 percent in private cloud, New Zealand data centres and public cloud.

Just 15 percent used offshore data centres.

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