Applied observability or data observability is a tool used to understand an enterprise’s data systems completely. You see, enterprises heavily rely on their data for major business decision-making and operations. Therefore, they must have the latest and high-quality data in hand. It is where data observability comes into the picture. 

With well-applied observability, businesses get clear visibility into their data pipelines. It empowers the teams to develop processes and tools to apprehend how data flows in an enterprise. It also helps in identifying the bottlenecks and preventing data inconsistencies and downtimes. Keep reading as we delve deeper into this technology and understand the factors that are making it a leading monitoring trend. 

state of data observability 


What is Making Applied Observability a New Trend?

Data observability helps boost the entire data operation processes by:

  • Enhancing the usefulness, quality, and comprehensiveness of the data for more precise decisions with full context. 
  • It also ensures that the data is timely delivered to the concerned department. 
  • It helps in delivering higher trust in data. The result is that enterprises can make more informed data-driven actions. 
  • Data observability also helps improve the responsiveness of the data operations team to the enterprise and meet the organizational goals
  • Applied observability also helps in SLA tracking. It can assess the pipeline data and data quality against predefined benchmarks. 
  • Data observability is beyond alerting and monitoring. It allows businesses to understand their data systems, helps them fix data issues, and proactively prevents them. 

What are the Drivers Behind Applied Observability? 

The modern digital economy and digital transformation have exponentially boosted the data volumes used in enterprises. As per the latest reports of IDC’s Global Datasphere, over 59 ZB of data was generated, copied, captured, and consumed by the world in 2020. 

And it also predicts that this growth will continue through 2024 with a CAGR of 26%. Another contributor to this IT monitoring trend is the increase in data replication across enterprises, usually for analytics. Over 70% of organizations will use this technology by 2026 to attain shorter dormancy for decision-making. It will also help them gain a competitive edge in IT processes. 

Along with this, enterprises are also concerned about the security of their confidential data. Going for a digital immune system can be a wise idea here.  Managers should meet the experts to understand how the new digital immune system is helping enterprises in 2022. 

Moreover, a major portion of the data is transferred through emails. Knowing the best practices to avoid email security compromises can help enterprises protect their data.  

data observability cycle



So, this was all about data observability. It is an innovative way of monitoring, alerting, tracking, comparing, and analyzing data across the pipeline. Its ultimate motive is to provide crisp insights to organizations and help them make informed decisions and attain business goals. Enterprises should create a special team to handle data observability operations effectively. 


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