Data observability is a specific aspect of data management that gives organizations a comprehensive understanding of the health and state of the data within their systems. This helps to understand the relationships and interdependencies between data elements and components within an organization’s data ecosystem, including how data flows from one source to another and how it is used and transformed.

Why is Data Observability Important?

According to a recent Gartner Report Innovation Insight: Data Observability Enables Proactive Data Quality, data observability is a critical requirement to both support and enhance existing and modern data management architectures. Organizations that prioritize data observability are better positioned to harness the full potential of their data assets and gain a competitive advantage in the digital age.

If you haven’t done so already, here are a few of the reasons why you may want to prioritize data observability as a strategic investment:

1. Improved Decision Making: Data quality is an essential underpinning of a data-driven organization. Data observability helps organizations identify and rectify data quality issues early in the data pipeline, leading to more accurate and reliable insights for decision-making.
2. Less Downtime: Continuously tracking the flow of data from source to destination and having a clear view of data dependencies enables quicker issue resolution and minimizes downtime in data operations.
3. Lower Costs: Enterprise Strategy Group estimates that advanced observability deployments can cut downtime costs by 90%, keeping costs down to $2.5M annually versus $23.8 million for observability beginners. Real-time monitoring, early issue detection, and automated responses help organizations more proactively identify and address data issues, which reduces the cost of fixing downstream issues.
4. Greater Productivity and Collaboration: Data observability fosters IT collaboration and productivity by providing a collective understanding of data and its lineage, promoting transparency, and providing real-time feedback on the impact of changes.
5. Stronger Data Security: Data observability can improve security by enhancing an organization’s ability to detect, investigate, and respond to security threats and incidents. Real-time insights, comprehensive visibility, and automated responses enhance an organization’s overall security posture.
6. Regulatory Compliance: Monitoring and controlling data access helps organizations comply with data privacy and security regulations.
7. Change Control: Data observability helps manage changes in data schema, data sources, and data transformation logic by ensuring that changes are well understood, and their impacts are thoroughly assessed.
8. Accelerated Digital Innovation: Data observability supports digital innovation by providing organizations with the data-driven insights and change control needed to continuously experiment, adapt, and create new solutions. It can also optimize digital experiences by ensuring the reliability, performance, security, and personalization of digital services.
9. Operational Efficiency: By observing data flows, organizations can detect and resolve bottlenecks, errors, and inefficiencies in their data pipelines and processes.
10. Optimized Resource Allocation: By identifying which data components are most critical and where issues occur most frequently, organizations can allocate, manage, and adjust their resources more efficiently.

Summary

Data observability strengthens an organization’s competitive edge in today’s data-driven business landscape. It ensures that organizations can maintain data quality, which is crucial for informed decision-making. It allows businesses to proactively detect and rectify issues in their data pipelines, reduce downtime, and lower costs. By enhancing visibility into data workflows, organizations can foster greater collaboration and improve security and compliance. Data observability provides change control that makes digital innovation less risky and provides operational and resource allocation efficiency.

Getting Started with Actian

Incorporating data analytics into data observability practices can significantly enhance an organization’s ability to identify and address issues promptly, leading to more reliable data, improved decision-making, and a stronger overall data management strategy. The Actian Data Platform includes many capabilities that assist organizations in implementing data observability, including built-in data integration with data quality as well as real-time analytics. Try the Actian Data Platform for 30 days with a free trial.

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