Data Observability using Microsoft Fabric

How Microsoft Fabric Helps Implement Data Observability in Your Organization

By Gjnana Prakash Duvvuri  •  July 19, 2023  •  1200 Views

How Microsoft Fabric Helps Implement Data Observability in Your Organization

What is Data Observability

Data observability empowers organizations to grasp the vitality of their data systems, utilizing DevOps Observability principles to eradicate data downtime. Through automated monitoring, alerting, and triaging, it identifies and assesses data quality and discoverability concerns, fostering robust data pipelines, enhancing team productivity, and ensuring satisfaction among data consumers.

Five Pillars of Data Observability 

Data Freshness

Assessing the timeliness and update frequency of your data tables is crucial for informed decision-making. Outdated data equals wasted time and money.

Data Distribution

Understanding the range of possible values in your data provides insights into its reliability. Knowing what to expect from your data helps establish trustworthiness. 

Data Volume

The completeness of your data tables reflects the health of your data sources. Sudden changes in volume alert you to potential issues. 

Data Schema

Changes in data organization can indicate data integrity issues. Tracking schema modifications and their timing is key to maintaining a healthy data ecosystem.

Data Lineage

Pinpointing where data breaks occur is essential. Lineage reveals the upstream sources and downstream users affected, along with metadata essential for governance and consistency. 

Data Observability with Microsoft Fabric
Data Observability with Microsoft Fabric

Data observability is the ability of an organization to have broad visibility of its data landscape and multilayer data dependencies. It helps bridge the gaps in data governance, ensuring a well-rounded, comprehensive, and contextual approach to resolving bottlenecks and driving results.

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Key Components of Data Observability

Rapid Integration

Does it seamlessly integrate with your existing infrastructure without the need for pipeline modifications, coding, or specific programming languages? A swift and smooth connection ensures quicker benefits and enhanced testing coverage without substantial investments.

Security-Centric Architecture

Does it monitor data in its current storage location without necessitating data extraction? Such a solution scales across your data platform, ensuring cost-effectiveness and compliance with stringent security standards.

Simplified Setup

Does it require minimal configuration and virtually no threshold adjustments to get started? An effective data observability platform employs machine learning models to adapt to your environment and data automatically. By utilizing anomaly detection techniques, it reduces false positives by considering the broader context of your data, minimizing the need for extensive rule configuration and maintenance. Moreover, it allows you to define custom rules for critical pipelines directly within your CI/CD workflow, offering both simplicity and flexibility.

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Core fundamental foundations 

How Microsoft Fabric Helps Implement Data Observability in Your Organization

Conclusion

In summary, implementing data observability is crucial for organizations aiming to maximize the value and reliability of their data systems. By embracing the five pillars of data observability—data freshness, distribution, volume, schema, and lineage—and utilizing key components such as rapid integration, security-centric architecture, and simplified setup, organizations can achieve greater insights, productivity, and satisfaction among data consumers.

Microsoft Fabric, specifically Onelake, serves as a robust supporter of the data observability framework, offering core elements that benefit customers immensely. Its emphasis on time-to-value, security-first architecture, and minimal configuration aligns perfectly with the needs of modern organizations. By seamlessly integrating with existing stacks, ensuring data security at rest, and requiring minimal setup and configuration, Microsoft Fabric simplifies the path to achieving comprehensive data observability. With its inclusive and integrated approach, facilitated by one-tenant deployment, Microsoft Fabric emerges as a reliable partner in fostering a data-driven culture within organizations, ultimately driving success in today’s data-centric landscape.

Gjnana Prakash Duvvuri

Gjnana Prakash Duvvuri

Gjnana has an impressive 24 years of experience in IT, with a particular focus on cloud architecture consulting and IT technical leadership. He has worked with big-name clients such as Microsoft, Union bank(MUFG), Delta Airlines, BCBS, Macys, Global Payments, and UPS, supporting their large transformative initiatives. Over the last 7 years, Gjnana has been specializing in cloud platforms such as Azure, AWS, Oracle, and Google. His main area of focus is Digitalization Data & AI, Open Analytics, SAP Integration, Modern data warehousing with BI & AI on end-to-end implementations with data services, app modernization, and on-prem to cloud migrations. With his deep understanding of business domain operations in industries such as Financial Card Merchant Services, Banking, Retail, Supply Chain Management, Manufacturing, Pharmaceuticals, Pharma product management, Healthcare, Biotechnology, Oil & Gas, Travel and Transportation, Gjnana shares technical and domain knowledge through webinars and blogs.

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