Debugging Code, People and Habits: Tips for Better Data Quality Management

October 26, 2016 Kara Frazier

Man typing on laptop that's in his lap

In the era of Big Data, data quality is still a constant concern. Decision-makers want to collect as much digital data as possible from their customers’ online activity, but oftentimes they look at reports and question the numbers.

This is the data that’s supposed to drive strategic business decisions. If the quality of that data is not trustworthy, decision-makers could be jeopardizing their strategies on inaccurate information.

Believe it or not, the analytics platform your organization uses to collect customer data isn’t infallible. Even if you implement your analytics solution flawlessly, it won’t stay that way for long—websites are constantly being updated by multiple teams and business units.

Unfortunately, sometimes electronic solutions fail.

Whether through technological malfunctions or human error, the quality of your analytics implementations is frequently threatened, making your data unreliable and your decisions misguided.

So how do you maintain quality data?

At the Analytics Summit on November 17th, members of Team Demystified, Analytics Demystified’s full-time client support team, presented “Debugging Code, People, and Habits: Tips for Better Data Quality Management” to help analytics practitioners implement the most effective data collection practices to produce trustworthy data.

As Elizabeth Eckels puts it, “Having correct, quality data shouldn’t depend on your platform. It’s up to you, the analyst, to ensure you are collecting accurate data that your decision-makers can use to guide your organization.”

This Team Demystified panel includes four Digital Analytics Consultants: Elizabeth “Smalls” Eckels, Jonas Newsome, Cathy Morse and Nico Miceli.

View this presentation on-demand.


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