Every day, your business leverages data to make the right decisions both swiftly and strategically. Whether you’re gathering consumer analytics to kickstart a new marketing campaign or are looking for a way to identify opportunities to remain ahead of your competitors, data inevitably fuels your daily operations. But what’s even more important than the mere possession of data is ensuring that it’s clean and healthy – which is where data observability comes into play.
Data observability refers to a company’s ability to comprehensively understand the health of the data present within its systems. While data is pivotal to an organization's success, it requires a complex system to manage and proactively monitor. Below, we’ll go into deeper detail regarding data observability while outlining key reasons your business should prioritize best practices for ensuring the optimal health and state of your data.
What is data observability?
As noted above, data observability refers to the ability to comprehend the health and state of data present within your organization. What does this look like in practice? Observability includes more than just monitoring your data. Instead, it encompasses the set of workflows and tech in place to ensure you can quickly identify and resolve any errors in your data wherever and however they occur. This includes assessing the cause of the issue and putting the proper practices in place to ensure your system becomes continuously more reliable to reduce further risk.
While identifying problems in your data is crucial, data observability offers extensive background into the issues at hand to provide remedial measures that ensure the strength of your data quality standards and practices today and in the future.
The critical components of data observability
Overarchingly, data observability refers to the methods, activities, and data quality solutions used to better comprehend your data’s health. Since data “healthiness” is a blanket term that may hold different meanings to various individuals, we’ll cover some of the key pillars that are at the core of upholding data observability:
- Alerts: notices of both anticipated and unexpected events
- Logging: the recording of an event with details including timestamps and context surrounding the event’s occurrence, as well as what changes were made and by whom
- Monitoring: leveraging a program to continuously observe your business systems and pipeline
- Analysis: comprehending data to derive business insights and assessing necessary adaptations to integrate into your data health
- Tracking: measuring current and forecasted data quality against determined standards
When the critical activities for data healthiness and reliability are not only put in place but also standardized and well-integrated into your operational procedures, your business possesses the awareness and proactivity required to maintain the optimal state of your data.
How data observability benefits your business
Data observability is pivotal in a business's ability to remain on top of the data quality movement. But what exactly does this mean for your company? Below, we'll delve into some key benefits of this concept.
- Curate trusted and accessible data
The consequences of unmanaged and error-ridden data can be detrimental to a business. With data observability top of mind, there's an emphasis on data monitoring to ensure your business can confidently make data-related decisions. What’s more, data observability also offers a comprehensive view of data within the business’s data ecosystem, helping you to pinpoint data problems the moment they occur.
- Mitigate data issues quickly when they arise
Data problems happen and when they do, data observability equips your team with the know-how to localize the source of problems and errors in real-time to inform the best action plan for your business. This means that any complications that implicate unhealthy data or prospective data downtime can be identified and handled swiftly – a crucial act in ensuring your business can run according to plan each day.
- Avoid problems by recognizing anomalies in your data
At face value, your data processes may appear healthy and well-oiled. But beneath the surface, there may be certain circumstances present that you are unaware of, which can lead to prospective issues catalyzing a ripple impact on your business. Fortunately, data observability not only helps to address problems as they occur but also aids in their prevention altogether. With the correct information on hand to investigate root cause issues and the remediation to prevent them from manifesting into more significant problems, your business can intercept and halt crises from growing.
How Experian can help
Our team wants to empower our customers with the tools necessary to reach their business’s greatest potential – starting with the power of streamlined and clean data. Reach out to one of our data quality experts to learn more about our data quality tools and solutions today!
