INFOGRAPHICData Observability
What is data observability?
Data observability is the ability to understand, diagnose, and manage data health throughout the data lifecycle.
What it means for you, is the ability to be more proactive in tackling your data problems.
Artificial intelligence identifies data anomalies in real time, helping you take action faster and prevent costly downstream issues.
Data observability tools
are essential to ensure reliable data pipelines across data ecosystems and support data and AI initiatives.1
By 2027, 70% of enterprises implementing distributed data architectures will have adopted data observability tools to improve visibility over the state of the data landscape, up from around 50% in 2025.1
16 Best Practices to Implement Data Observability Tools for Data and AI Initiatives, September 2025
Top DataOps Drivers
Source: DataOps Survey, IDC 2021, N=401
What’s driving data observability?
Data observability has a big role to play in helping organizations achieve strategic objectives.
Here are just a few of the top drivers.
Investments Are Focused on AI for Data and Data for AI
Q. What are the overall organization’s top 3 strategic investment priorities for data in the next 12–18 months?
Source: IDC 2024 Office of the CDO Survey Technical Perspectives
Lack of data observability in action
We’ve covered the ins and outs of data observability, but maybe you’re still not sure why you need it. Here’s one example of how an unnoticed error can spiral and cause downstream issues that can go unsolved for months.
A 3rd party vendor sends a data file late, missing the upload to your internal system.
Error goes unnoticed.
March
Downstream, the analytics reports show a steep drop in sales revenue for the prior month.
April
The CEO is alarmed at the steep drop in revenue and calls an emergency meeting.
Sales leaders say they are not seeing a drop in their sales.
May
IT discovers the missing file is the cause of the issue.
Once rectified, reports show sales had actually INCREASED, but time was wasted.
June
With data observability, the issue could have been caught immediately – saving the organization time, confusion, and headaches.
Stop bad data in its tracks
Prevent bad decisions by using data observability to alert your teams about potential issues before they have downstream impacts.
The Precisely Data Integrity Suite: Data Observability service
We’re here to help you power better decisions with data observability.