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What is Data Observability?
Explore the key elements of data observability, and how it helps you take a more proactive approach to data quality and trust for bigger results.
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Data observability solutions
Minimize business disruption and prevent costly downstream data and analytics issues with data observability solutions – intelligent technology that proactively alerts you to data anomalies.
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Data Observability |
- Increase confidence in data-driven decisions
- Get visibility into data health
- Proactively identify and correct data issues
“Observability continuously monitors and tests data for drift and shift within acceptable tolerances defined by policy. Notifications are triggered when data falls out of bounds.” 1
-IDC
Catch problems before they impact your business
Working backwards to repair data issues can get very expensive, very fast. But what if you could catch these problems in real time, fix them faster, and cut costs?
That’s where data observability can help. To determine whether it suits your organization’s needs, ask yourself the following questions:
- Are data-driven decisions becoming even more important in your organization?
- Have you ever had a report with inaccurate data get to our executives before anyone realized there was an issue?
- Is your organization relying more on advanced analytics for recommendations?
If any of these issues sound familiar, your organization can benefit from a data observability solution. As part of an overall DataOps strategy, data observability enables trust in your data and analytics. Data observability ensures data reliability by monitoring your organization’s data, performing analysis to determine current and potential adverse data events, and alerting those who need to resolve the issues.
“Data observability improves reliability of data pipelines by increasing our ability to observe changes, discover unknowns and take appropriate actions.” 2
-Gartner
Importance of data observability
Trust in data is vital for today’s enterprises, which are using analytics to identify strategic opportunities and feeding AI/ML models that automate decisions. Data observability plays a powerful role in ensuring that data is reliable, providing these key benefits:
- Proactively eliminate risks associated with inaccurate analytics. By detecting anomalies and automatically alerting the appropriate users to possible problems, data observability empowers organizations to be proactive rather than reactive, addressing data issues that have the potential to disrupt the business and create costly downstream problems.
- Reduce the time to solve operational issues. Data observability provides vitally important information that saves you time and headaches. Effective solutions provide tools like lineage – which enables you to trace the root cause of an issue, along with remediation options that help you resolve those issues quickly.
- Minimize the cost associated with adverse data events. Data issues can cause significant impact. The longer before anyone realizes the issue the more damage that can occur. By proactively identifying issues and eliminating them the impact is minimized or eliminated.
- Effectively support digital transformational initiatives. Digital transformation is a top priority for many businesses, but they inevitably involve more data and more rapid change than ever before. Data observability empowers data engineers and other users with a critical understanding of what’s happening to your data.
“By 2026, 30% of enterprises implementing distributed data architectures will have adopted data observability techniques to improve visibility over the state of data landscape, up from less than 5% in 2023.” 3
-Gartner
“Observability is the missing piece today to give our data stewards access to data discovery insights without having to go to IT for queries or reports.”
Jean-Paul Otte, Chief Data Officer Degroof PetercamData Observability Module
Learn how Precisely can help with data observability challenges using the Data Observability module of the Data Integrity Suite.
Learn more about Data Observability
1 IDC, Phil Goodwin and Stewart Bond, “IDC Market Glance: DataOps, 2Q21” (June 2021)
2 Gartner, Hype Cycle for Data Management, 2022, Melody Chien, Ankush Jain, Robert Thanaraj (June 30, 2022)
3 Gartner, Innovation Insight: Data Observability Enables Proactive Data Quality, Melody Chien (July 2023)