The Three Stages of Data Observability Maturity
Whilst there is clearly value in adopting data observability, many of the solutions will still require data professionals to deploy and operate them and to put fixes in place when issues arise. What if automation could be put in place to minimize the need for human intervention between the data observability solutions and the data pipelines, databases, warehouses, lakes and business applications? This is where data observability is heading, and it will bring even greater time and resource savings to those organizations that are willing to invest.
Adopting data observability isn’t necessarily straightforward. It’s not about buying an off-the-shelf solution or tool; it involves a combination of cultural change, new tooling and integrated solutions that come together to deliver the benefits discussed here. To help with its adoption, organizations should look at breaking down their observability goals into three stages of increasing maturity:
- Monitoring and Alerting – Organizations should first plan to implement solutions that identify data issues in real-time and alert the stakeholders responsible for fixing them.
- Analyzing and Reporting – Organizations can then look to augment the basic monitoring and alerting capabilities with additional ones that allow their data users to quickly identify the root cause of any issues.
- Automation and Control – This is the peak of data observability maturity. Once there are solutions in place for monitoring, alerting and analysis, organizations should implement automated solutions for fixing issues. Data observability stewards can control automated workflows to ensure they’re working in the desired way, but ultimately, they (and data users) will spend significantly less time fixing data and pipelines, and more time using them to run their business.
In summary, the more mature an organization’s data observability practice, the fewer resources it spends fixing and maintaining operational and analytical data infrastructure, unlocking major value for SMBs.
Organizations are only recently beginning to discover the benefits of data observability solutions. While many early adopters might be larger enterprises, SMBs are sure to follow in their footsteps and some are already doing so. The benefits are available to everybody, but those smaller and more agile organizations will be able to realize the value faster, as they will get immediate benefits from knowing what issues they have in real-time, knowing the root cause of them and knowing how to fix them before they see any serious business impact from unhealthy data.
Looking into the future, organizations will start to see additional benefits from intelligent observability solutions through the automation they bring that will alleviate the frustrations of working with data that many data professionals deal with today.