What is it and why is it important?

What is data observability

Today, data is one of a company’s most valuable assets because the insights it provides enable critical decisions. This data must be accurate, high quality and reliable. While it is essential to gain insights into data, it is also vital to understand the health of your data to ensure it is not missing, misused, or incorrectly added. With data observability, your business can manage, track, and identify issues with its data systems and data before they cause downtime.

A. What is data observability?

Data observability involves an organization’s ability to fully understand the state of its systems and data. With excellent data observability, your business gains complete visibility of its data pipelines. It also enables teams to create processes and tools to understand the flow of data across the business and spot data barriers to avoid inconsistencies and downtime.

B. Importance of data observability

1. End-to-end data pipeline view

Data Observability provides an end-to-end view of the data pipeline while eliminating data downtime using best-in-class DevOps and pipeline observability principles. This means applying alerting, triage, and automated monitoring to detect and assess data quality and discoverability issues.

Dealing with a broken data pipeline or data problem can be difficult. When your team doesn't know that something is broken in the data pipeline or that data is corrupted, they risk compromising experiments, stakeholder trust, and the integrity of analytics.

With a data observability platform like Streamdal, your DevOps team can get an end-to-end view of the data pipeline, allowing them to react in a split second when things go wrong. It also allows them to see beyond performance metrics by giving them answers about the reasons for failures.

2. Overview of data system health and performance

Data observability helps your team ensure the health of your data by maintaining a constant flow of its volume, distribution, metadata, freshness, and lineage. Businesses with a large number of disconnected tools can use observability monitoring to help IT gain insights into the health and performance of your system.

One of the main benefits of data observability is the streamlining of root cause analysis. It allows you to enable end-to-end data monitoring and visibility across a complex IT architecture so your teams can easily detect data issues and bottlenecks, regardless of their origin.

3. Eliminates the risks of inaccurate reporting and analytics

Data observability allows businesses to detect irregularities and automatically alert the right users of warnings that could lead to dangerous data events. This can make your business more proactive in handling potential data issues that disrupt your business and develop costly problems downstream.

4. Increases confidence in data for critical business decisions

While machine learning algorithms and data insights can be beneficial, poor data management and errors can be disastrous for your business. However, data observability allows your business to quickly monitor and track situations, which builds confidence when making data-driven decisions.

5. Ensures the accuracy, quality, reliability and value of data.

Your data team can use data observability to ensure that the accuracy, quality, reliability, and value of data are not compromised. It can also help them ensure that data pipelines are not broken. Without a comprehensive data observability strategy, analytics and data teams may struggle to ensure pipeline reliability and data consistency with an agile, iterative methodology or conduct root cause-centric analysis that enables to find quick and effective solutions.

C. Endnote

Data observability is essential for any data-driven organization. Consider investing in data observability to benefit from these benefits.