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How Data Profiling Can Reduce Burnout

4 MIN READ
3 MIN READ
April Yep

7.17.24

April has several years of experience in the observability space, leading back to the days when it was called APM, DevOps, or infrastructure monitoring. April is a Senior Product Marketing Manager at Mezmo and loves cats and tea.
4 MIN READ
3 MIN READ

One of the most common sentiments across the industry, let alone this world, is burnout. Burnout is prevalent, the World Health Organization (WHO) estimates it costs the global economy $1 trillion dollars a year. A Gallup poll equated that to $3,400 lost for every $10,000 of salary due to lack of productivity. This problem isn’t ending anytime soon either, with the global Cybersecurity industry alone having a talent shortage of 4 Million people

Why am I talking about this? Many tech roles—Site Reliability Engineers, Cybersecurity professionals, Software engineers, etc.—experience burnout on a daily basis. That page you got at 3 AM, or that error message you received, is because some of the data flow is not working as expected. Add in that you are likely understaffed, so you have to go online and review telemetry data. The problem that makes burnout greater is the amount of telemetry data you have to go through to find the needle in a haystack—logs, metrics, events, traces, etc. Then once you have that data, you have to hope it’s configured correctly and is getting the right signals—queue in data profiling for telemetry data. 

What is data profiling?

Per Gartner, “Data profiling is a technology for discovering and investigating data quality issues, such as duplication, lack of consistency, and lack of accuracy and completeness.” To put this in a telemetry data context, data profiling helps unlock the value of your data by identifying patterns, volume-drivers, high-value data elements, so on and so forth. 

Okay, data profiling, so what? Think reduced mental toil.

You're probably thinking, what does this have to do with burnout? 

The answer is that it helps you spend less time understanding how things work, and more time focusing on big projects and how to improve your services —reducing the mental toil it takes to identify, troubleshoot, and resolve issues. For example, imagine you have to explain to your peers how the telemetry data collected from your services works when something breaks. Add in that your organization is constantly making deployments—micro changes that may not impact your workflows significantly now—but could be a factor in the next deployment. 

While you may generally know your data well enough, you may not know how your data isn’t giving you the intended results. This is where data profiling comes in. 

Data profiling gives you a sense of the past, present, and future of your data, so you don’t have to do all the memorizing, troubleshooting, and guessing. You now have a clearer state of things and make the right decisions on how to handle your telemetry data.

While data profiling won’t prevent all surprises with your telemetry data, when the average developer is spending 57% of their time troubleshooting, any reduction in mental burden is appreciated so more time is spent on projects. Save yourself (and your team) from burnout. Check out our data profiling offer

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