Data engineers are passionate about creating new pipelines, developing cutting-edge solutions, and solving tough data challenges. But let’s be honest, maintenance is another story. It’s the repetitive, time-consuming upkeep of systems that, often, no longer serve a purpose.
In today’s data-driven organizations, data debt can accumulate quickly. So, what started as a high-priority data product can eventually fade into irrelevance — without anyone notifying the data team. Unfortunately, this results in wasted time, effort, and money.
The core problem lies in the fact that these outdated data assets are still being maintained and monitored as part of ongoing data quality efforts. This creates data debt, where a large portion of your data team’s time — up to 30% — is spent on managing assets that no longer deliver any real value to the organization. Instead of focusing on innovation, data engineers are often wasting their time and energy on maintaining obsolete pipelines.
The Non-Productive Chores Draining the Brains of Data Engineers
If you are a data engineer, I am sure you have been there. You are enjoying your coffee, when you receive an alert. Job error. The dreaded notification that something in your pipeline has gone wrong. It is always something that raises the heartbeat of every data engineer.
You rush to your desk, trying to fix the problem before the business team arrives and starts asking questions. After several hours of poring over logs, investigating dependencies, and checking the job flow, you find the issue. Another hour later, the error is finally resolved.
Good job? Maybe. But then you realize something unsettling.
If you trace the flow of this job pipeline, you’ll notice that it produces a table consumed by another job, which produces yet another table, and so on. It’s a long, complex chain of dependencies. But here’s the kicker — when you check the end product, a BI report, you discover that no one is actually using it anymore.
You couldn’t have known this by just looking at the jobs or tables — they still have “usage” through automated processes. But the data product, the final output that was once crucial to the business, hasn’t been touched in months. A year ago, when you built it, it was a high-priority project. But like many things, after six months, priorities shifted, and the need for this report disappeared. Yet, no one thought to tell you.
The Cost of Maintaining Unused Data Products
Here’s the painful truth: the half a day you spent debugging could have been avoided. You just spent hours maintaining a job that no longer serves any actual business purpose. And it’s not just your time being wasted — your company is also paying for storage, compute resources, and engineering hours to support a data product with zero usage.
This isn’t an isolated case. Over time, data engineers end up maintaining dozens, if not hundreds, of such products — jobs that are triggered on schedule, generating tables and reports that no one looks at anymore. These zombie data products drain your resources without adding value. And drain the job satisfaction of data engineers who want to be adding value and innovating.
How Can You and Your Team Avoid This?
It’s a situation all too familiar to data teams — maintaining outdated data pipelines for products that no longer serve any real purpose. But it raises important questions:
- Why are we keeping data products (and paying for them) after their usage has dropped to zero?
- How can we avoid accumulating data debt and ensure we clean up these unused pipelines before they become a burden?
- What tools do we need to track real-time usage at the data product level so that we can optimize our resources and eliminate waste?
Empowering Data Engineers to Build the Future Rather Than Maintain an Irrelevant Past
This is exactly where Seemore Data steps in. We provide a platform that gives data teams complete visibility into their data pipelines and products. By tracking real human usage at the data product level, Seemore helps you identify which products are adding value and which ones have become obsolete.
With Seemore, you can:
- Identify unused data products quickly, so you’re not wasting time maintaining them.
- Clean up dead pipelines and avoid the accumulation of data debt.
- Save costs on resources by eliminating jobs and data products that no longer deliver value.
- Optimize your data operations, so your team can focus on building, not maintaining.
Avoiding the Maintenance of Non-Relevant Data Products
As data engineers, we thrive on innovation and building new systems that solve real business problems. But the key to sustaining that momentum is ensuring that we don’t get bogged down in maintaining products that are no longer relevant. By embracing data transparency and real-time visibility with Seemore, you can stay ahead of data debt, optimize your operations, and keep your team focused on what they do best — building the future.
Are you interested in continuing this discussion directly with Ariel? You can message him at ariel@seemoredata.io to delve deeper into ensuring your data teams don’t waste time on data assets no one is using.
