With the challenges created by the influx and complexity of today’s data, companies are increasingly looking for help to understand the health and reliability of their data. The need for capabilities beyond traditional tools have given rise to data observability for continuous monitoring and automated detection of problems related to data quality and workloads delivering data.

Gartner estimates that 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.” 

In this Gartner® Innovation Insight learn:

• The 4 critical features of data observability
• The 5 critical technologies to create a data awareness AI engine
• The roles of data observability and data quality
• The benefits and uses for data observability
• Recommendations for data and analytics leaders looking to enhance data quality and governance practices with data observability

If you’re considering incorporating data observability into your organization to improve data quality and reliability, check out this report.

Gartner, Innovation Insight: Data Observability Enables Proactive Data Quality, Melody Chien, 20 July 2023

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