Did you know that data governance and data observability are interdependent?
While data governance establishes the rules and standards for data management, data observability ensures those rules are followed in real-time. Together, they create a feedback loop that reinforces data trust and AI readiness.
This blog post will discuss the benefits of using a Data & AI Governance Platform like DataGalaxy with a data observability platform like Bigeye to create a unified, best-of-breed data governance and observability experience, enabling organizations to deliver clean and trustworthy data to their data teams at scale.
DataGalaxy and Bigeye bring the power of a unified, best-of-breed data governance and observability experience, enabling organizations to deliver clean and trustworthy data to their data teams at scale.
Our unique solution is designed to seamlessly integrate with existing data sources to create a centralized data inventory and provide a deeper understanding of data quality.
This offers a fully configurable, out-of-the-box operating model that helps data teams efficiently catalog their data inventory, add business context to metadata, track end-to-end lineage, establish ownership, workflow management, and monitor data quality with alerts for ongoing governance and quality maintenance.
There are several implementation options for data governance and data observability:
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Example technologies: Uber, Airbnb, and Netflix started with homegrown solutions that evolved as the organizations scaled. However, they eventually shifted to more robust third-party platforms to manage data governance and data observability at scale.
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Example Technologies: IBM, Informatica, and Microsoft offer comprehensive data governance and data observability platforms that aim to provide a one-stop solution for organizations.
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Example Technologies: DataGalaxy and Bigeye are examples of specialized vendors that, when integrated, offer a powerful solution for both data governance and data observability, ensuring comprehensive coverage across the organization’s needs.
The combined value of DataGalaxy and Bigeye includes:
DataGalaxy provides comprehensive data cataloging and lineage
The combined approach builds confidence in data for AI initiatives
Bigeye ensures complete visibility of pipeline health and data quality
Seamless connection between platforms creates an end-to-end solution
Key product highlights include:
Building AI readiness and data trust requires a strategic approach to data governance and observability.
By implementing these strategies, organizations can ensure data reliability, improve operational efficiency, and unlock the full potential of AI.
The combined value of best-of-breed solutions like DataGalaxy and Bigeye provides a comprehensive foundation for achieving these goals.
Data governance is the practice of managing data to ensure it’s accurate, secure, and used responsibly across an organization. It sets the rules, roles, and processes for how data is defined, accessed, and maintained. It involves creating clear policies, assigning data ownership, and establishing standards for how data is handled throughout its lifecycle.
Data governance brings order to the chaos by making sure everyone uses and understands data the same way. Without a solid data governance foundation, it’s hard to trust data or use it effectively, and that can hold a business back.
However, It’s not just about control. Data governance is about enabling better collaboration and smarter decisions across teams. When data governance is done right, it turns data into a trusted asset that drives innovation and growth.
Implementing data governance starts with clearly defining your goals—whether it’s improving data quality, ensuring compliance, or enhancing decision-making—and determining the scope of the initiative.
Establish a governance framework by assigning key roles such as data owners, data stewards, and a data governance council. From there, develop policies and standards that cover data access, privacy, quality, and consistency to ensure data is well-managed across the organization.
It’s also vital to utilize tools like data catalogs, metadata management platforms, and data quality solutions to automate policy enforcement, track data lineage, and provide visibility into data assets.
Information governance is a comprehensive framework that governs the management, utilization, and protection of an organization’s information assets in alignment with regulatory, legal, and operational objectives.
It integrates policies, standards, roles, and technologies to ensure information is accurate, secure, and used ethically throughout its lifecycle. Robust information governance enhances compliance, mitigates risk, and enables strategic value creation from enterprise data.
To start a data governance program, begin by identifying key stakeholders, setting clear objectives, and defining data ownership and policies. A successful data governance program requires alignment between business and IT to ensure data quality, compliance, and strategic value from the outset. It’s important to do research on what makes up a good data governance structure – Here are some sources to get you started.
