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6 Signs You Need a Data Observability Tool

September 8, 2022

Co-founder / Data and ML

September 8, 2022
6 Signs You Need a Data Observability Tool

As data observability tools grow in popularity, many data leaders are asking themselves, “Does my team need one?” 

Sadly, no one can answer this question for you. To do so, you must evaluate your unique business needs, goals, and challenges. Only then will it become clear whether an investment is warranted. 

In this blog post, we highlight six signs you need a data observability platform. But first, we wanted to share three signs you don’t need one (at least not yet):

  • Your company is just getting started with data. If you’re still working to collect and store data at your company, that should take priority. Once data is flowing into your systems is a better time to bring on data observability. Just don’t wait too long, or your data quality will suffer and stakeholders will lose trust.
  • Your company doesn’t value being data-driven. If you’re collecting, storing, and using data, but it isn’t valued by your business counterparts, then your top priority should be establishing a link between data and business performance. Start by conducting user interviews with key stakeholders, then educate them about its connection to desired business outcomes.
  • You don’t have clear use cases for data observability. Once you’re using data and it’s valued at your organization, it’s almost time to bring on data observability to preserve stakeholder trust and increase your team’s leverage. But, before you do, outline why it matters to your business. What jobs will a data observability tool empower you to do? What outcomes will it drive you to achieve?

If you collect, store, and use data; it’s valued at your company; and you’ve established clear use cases, you can confidently move on to the signs you need a data observability tool below.

1. Your data impacts the company’s bottom line

All businesses aim to increase revenue, reduce costs, and mitigate risk. They bring on data teams to drive more informed decisions and effective actions in service of these goals. 

The degree to which data is tethered to business performance varies. On one end of the spectrum, you have companies that leverage data to support strategic decision-making. In this case, the cost of poor-quality data is the cost of a poor decision. On the other end of the spectrum, you have companies that leverage data for customer-facing operations. In this case, low-quality data has a direct impact on a company’s performance. 

While getting to know hundreds of data-forward companies, we’ve discovered that the more a company uses data to fuel their operations, and the fewer people who have their eyes on the data, the more a data observability platform is needed. 

Data observability platforms can correct the asymmetry between the resources and responsibilities of modern data teams. I’m referring to the fact that headcount rarely increases at the same rate as the company’s growth. As a result, it’s imperative that data teams maximize their leverage—something a data observability tool is designed to help with. 

2. Your stakeholders flag data quality issues

Modern data technologies may have made it easier to collect, transform, and use data, but that doesn’t change the fact that data teams are responsible for hundreds to thousands of data assets, from upstream tables to downstream dashboards. 

Stakeholders, on the other hand, only care about one data asset—the dashboard they view day and night. As a result, and because they have the domain expertise to know when something looks wrong, stakeholders are often the first to discover silent data bugs. 

If your stakeholders are usually the ones to flag data quality issues, you could benefit from a data observability platform. These tools notify you instantly when an anomaly is detected, and empower you to quickly investigate said issue to determine its root cause and impact. 

3. Your team operates in the dark

When a stakeholder pings you about a broken dashboard, you likely follow these steps: 

  1. Determine whether it’s a real issue, ideally through corroboration 
  2. Evaluate its impact on data assets and stakeholders
  3. Inform stakeholders and provide a timeline for fixing the problem
  4. Investigate until you’ve identified its root cause
  5. And finally, fix the issue

In sum, you need to identify whether it’s a real issue, investigate the root cause, and determine the impact. How easy is that for your team today? And, how long does it take you?  

If you find yourself digging around like Sherlock, trying to find the appropriate metadata, for a lengthy period of time, it might be time to invest in a data observability platform. These tools collect and centralize all of your metadata in one place, providing actionable insights that help you do your job more efficiently and effectively. 


4. You rely on intuition to make decisions

Contrary to popular belief, data teams do not exist to solve data issues. As already mentioned, they ultimately exist to drive revenue growth, cost savings, and risk mitigation. Despite this, many teams prioritize firefighting over higher-value projects with long-term benefits. 

Ask yourself: Are your team’s priorities influenced by ad hoc requests or your hunches about which data asset deserves your attention at any given moment? If you answered yes, you probably need a data observability platform. After all, these tools provide the metadata you need to prioritize your work and allocate resources with confidence. 

5. Your team is rapidly growing

Another reason to invest in a data observability platform is if your team is growing rapidly.

As you know, it’s challenging to hire experienced data practitioners—in part because the industry’s most in-demand skills change so quickly. You therefore want to provide a good onboarding experience to new employees. That typically requires giving them an overview of your data infrastructure and showing them how everything’s connected—something a data observability tool can help with.

You also need to make sure new team members have the best experience possible once they’ve ramped up. Otherwise, you may lose the talent you’ve worked so hard to attract. And, the thing is, no one wants to spend all their time fighting fires. Instead, they want to leverage their autonomy to do intellectually engaging, high-impact work. Data observability platforms not only take menial work off your plate, they also help teams get their questions answered quickly, which enables them to take action sooner. The result is more satisfied employees who stick around longer.

6. Your team isn’t growing fast enough

Ironically, if you’re not expanding your team, it’s also important to adopt a data observability tool. As already mentioned, modern data technology has evolved to allow practitioners to have a greater impact with less effort. Knowing this, many leaders are intentional about choosing to keep headcount low. 

When Erik Edelmann first joined Vendr as Head of BI and Analytics Engineering, he wanted to maximize his team’s impact while minimizing overhead—something he felt was in the company’s best interest. That informed his decision to invest in a data observability platform. Today, he describes it as the command-and-control center that delivers a comprehensive view into the state of his data.

A sign of good things to come

Every company is unique, but certain trends hold true across companies that impact the need for data observability. If your data fuels company growth, your stakeholders are the ones flagging data quality issues, and your team operates in the dark or uses intuition to set priorities, it may be time to evaluate what data observability platform is right for you. These tools will provide the metadata you need to work efficiently, help you catch data quality issues as they happen, and maximize the leverage of your team, no matter its size. 

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