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We all know that using data well is key to success, but how can a semantic layer build on this success? For modern businesses, having good data governance and management systems is a must. These tools help clarify data, support smart decisions, and improve business processes.

But as amazing as all this data is, it’s worthless if your teams don’t understand it.

Most professionals aren’t technical experts in data engineering or data analysis - But that shouldn’t stop them from drawing insights from a business’ data. To understand a company’s raw data, it’s crucial to provide a business-friendly view that allows anyone in your organization to quickly and easily find answers to their business questions.

This blog post will discuss how modern technology professionals can use a semantic layer to better understand the information stored in their data catalogs for smarter, data-driven decision-making.

What is a semantic layer?

A semantic layer is a function that connects complex data systems with business users by using uses common language and business terms and keeps data consistent. This makes data easier to understand and use for business needs.

Functions of the semantic layer

The semantic layer acts as a middleman between raw data and tools for end-users. It changes complex data into terms that are easy for business people to get. Its main functions are:

Providing a unified and consistent view

of data across various platforms

Simplifying data interaction

by translating technical jargon into business terminology

Enhancing data consistency

and reliability for accurate business insights

Supporting user-centric data exploration

and analysis

Semantic layer key features

Good semantic layers have key features that simplify user experience, including:

User-centric design

Made for business users, offering easy data access and handling

Query translation

Changes complex data queries into terms that make sense for business

Maintenance of a business glossary

Keeps all data terms and definitions the same across the company, improving data consistency and communication

With these features, semantic layers make data easy to get to and useful. This helps in making better decisions by having consistent and reliable business terms.

The benefits of using a semantic layer

The semantic layer enables consistent, company-wide understanding and definitions of your data, ensuring everyone’s using the same internal language to describe the same thing. This makes your data easier to find and understand across your business and prevents a loss of time, duplicate work, and searching for information.

The semantic layer also dramatically simplifies queries by creating a logical view of your data using business-friendly terms. The semantic layer skirts the complexity of your vast amounts of data, empowers everyone in your organization to find exactly what they’re looking for, and ensures you’re all speaking the same data language.

More benefits of using a semantic layer include:

  • Simplifying data integration and abstraction: The semantic layer consolidates data from multiple sources, abstracts the technical complexities of data sources, and provides a unified view of data.

    Data engineers can use the semantic layer to integrate data from disparate sources such as databases, data warehouses, and data lakes, eliminating data silos and creating a unified view of data. This simplifies the data integration process, allowing engineers to efficiently combine data from diverse sources and make it accessible to data analysts and other business users.

  • Enhancing data understanding and accessibility: Semantic layers provide a common business vocabulary familiar to business users, bridging the gap between technical data and business users and enabling them to access and understand data easily.

    They define business objects and their relationships, creating a semantic model representing the underlying data in business terms. This business representation empowers using self-service analytics and BI tools to explore and analyze data in a way that aligns with familiar business terms, meaning business users can understand the data without needing technical expertise.

  • Facilitating data governance & security: Data governance and security are critical aspects of data management. The semantic layer ensures data consistency and accuracy by applying business rules and logic at the data layer. This helps maintain data integrity and enforce data governance policies across the organization.

    Additionally, the semantic layer provides a secure access layer, allowing organizations to control and manage data access based on user roles and permissions. This ensures that only authorized users can access the data, enhancing data security and compliance.

Data that speaks your language

Multilingual AI: Breaking language barriers for effortless data collaboration

DataGalaxy’s commitment to making data knowledge accessible drives our innovation. By integrating advanced translation and multilingual search capabilities into our Data Knowledge Catalog, we’re breaking down barriers in data understanding and use, fostering a truly global, data-driven culture.

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Integrating a data catalog & semantic layer

Combining a data catalog and a semantic layer is key for a smooth data management system - These tools work together to make data processes efficient and effective. This setup makes cross-system functionality easier, reducing the hassle of managing different systems.

When these elements work together, they boost reporting accuracy and help make better decisions and consistent data governance practices. Organizations can make data integration easier by linking a data catalog with a semantic layer and a data warehouse, simplifying finding, getting, and using data across different platforms.

Conclusion

A well-implemented semantic layer is a game-changer for modern businesses, making data more accessible, understandable, and actionable.

By bridging the gap between complex data systems and business users, it ensures consistency, simplifies queries, and enhances overall data governance. When integrated with a data catalog, the semantic layer creates a seamless, efficient data management system that empowers organizations to make smarter, data-driven decisions.

In an era where data is a critical asset, leveraging a semantic layer is no longer optional - It’s essential for unlocking the full potential of business intelligence and analytics.

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