Three Ways You’ll Know You Have a Data Quality Problem

The dashboards might be (mostly) green, the regulatory reports are being filed ok, but you’re looking around you and you’ve got a nagging feeling all is still not well with your data. Sound familiar?

Three Ways You'll Know You Have a Data Quality Problem
Welcome to frown town

You’re not alone. In this blog we’ve taken a look at some of the most influential factors that indicate you’ve got a data quality problem, as well as some handy ideas as to how to get them fixed.

Top of the list is negative feedback from your business partners.

This might not even be recorded or reported as a data problem, but if your business partners aren’t happy, it’s usually something to do with data. Data leaders have a long-held commitment to deliver all the required datasets to key functions with the desired quality, and this is always driven by the business goals that teams possess. Ultimately, it’s all about the data. But never fear! All business partners need is to be able to express what they’re seeing in the context of data management. In the film Passengers (spoiler alert! – if you’ve not seen it, go and watch it and then come back!) the central computer is showing ‘green’ metrics on a number of factors, suggesting all is well. Yet when they ask it different questions, they’re shown some critical metrics that are about to result in the destruction of their ship. If business teams can rapidly build PowerBI or Tableau dashboards (or any other visualisation tool, for that matter) that are completely aligned with their business goals and are linked to data elements, then they will be able to understand the criticality of data quality to their business line.

Secondly, you keep getting things sent to you in Excel.

Now, we all love Excel. It’s brilliant. It’s made data handling a far more widespread expectation at every level of an organisation. But it does not give any way of source or version controlling your datasets, and is massively prone to its inherent limitations in scale and size. In fact, its ubiquity and almost unilateral adoption means that all your fabulous data lake investments are being totally undermined when things like remediation files, or reports, get downloaded into an Excel sheet. If you’re seeing Excel being used for these kinds of activities, you can bet you’ve a data quality problem (or multiple problems) that are having a real effect on your business.

Third, your IT team has more tickets than an abandoned car.

If your business teams aren’t getting the data they need, they’re going to keep logging tickets for it. It’s likely these tickets will include change requests (to get the specific things they need), service requests (for a dataset or sets) or issue logs (because the data is wrong). More than an identifier that the data’s not great, this actually shows that the responsibility for accessing and using the data remains in the wrong place. It’s like they’re going to a library with an idea of the plot of the story, and the genre, but they can’t actually search by those terms so they’re stuck in a cycle of guessing, of trial and error. If you created an interactive dashboard or found a user-friendly interface that allowed the business users to access the data themselves, that would save everyone a whole heap of headaches. Of course, it would have to have all the source control and audit validation features that we flagged above, but it would streamline the access to data quite rapidly and reduce the burden on IT.

your IT team has more tickets than an abandoned car
A bit of a fixer-upper
picture of Matt Flenley
Matt Flenley
Marketing Insights

What else have you found that has shone a light on the dark corners of data? Drop me a line on LinkedIn and let me know what’s worked for you!

To learn more about how how Self-Service Data Quality is the best approach to developing a next-gen data management strategy, catch our webinar from 2020 with key input from CTO, Alex Brown (or read a blog post version here).