What Is A Semantic Layer, And What Does It Do?

Need for Smart Semantic Layer on Cloud - Kyvos Insights

While working with Business Analytics and Business intelligence, you may have seen software that works by using a semantic layer to run correct business reports.

This semantic layer is a method to represent data while using regular business terms. It takes the information stored in the data and translates that into terms that can be meaningful to them. So, if you wish to know more about the semantic layer, here is some information.

What is a Semantic layer?

The semantic layer helps map complex enterprise data into known or familiar business terms and offers a consolidated and unified view of data across systems. Most organizations struggle to manage and access their data properly.

However, about three-quarters of that data can never get analyzed or used. Thus, many businesses have a big gap between business users and data sources. A semantic layer can help those organizations to bridge this gap.

The semantic layer is the business representation of data, which allows end-users to discover and access data fast by using standard search terms like the prospect, recent purchase, customer, etc. it also offers terms to human-readable data sources.

How can a Semantic Layer Help?

There are various ways in which a semantic layer can help organizations. Some of those are:

  • Improved Governance and Security

While working with data, one of the biggest issues you may face is security and accessibility. If you increase the security too much, analysts will be unable to perform their tasks.

They will try to ignore the security rules to create several copies of data, which can compromise the integrity of the data eventually. If you add little or no security, your enterprise will be compromised.

A Semantic layer can offer a perfect balance between those two requirements. Users can make changes to the data while admins do not need to worry about the corruption of data sources.

  • Enhanced Collaboration

With the help of a robust Semantic layer, teams can work more effectively. They can easily search, tag, and share data and eventually improve collaboration across the entire organization.

What is a Semantic Layer? How to Build it for Future Data Workloads?

Thus, those teams can make better decisions. A semantic layer can remove the complexity of the procedures like analyzing, finding, and even sharing data. This helps everyone to work in an easier way than before.

  • Reduces Data Latency

Some data have a shelf life and can become worthless if not used within a particular time. This is more important in IoT environments like logistics and manufacturing.

A semantic layer can accelerate time to provide insight and consistent results and secure access to data while removing the need for complex data pipelines and helping businesses to gain value faster from all of their data.

  • Self-Service Reporting

While working, many organizations need to generate data in various sizes and shapes, and that data can be stored in various repositories like Microsoft ADLS and AWS S3 buckets.

Without the help of a semantic layer, users have to create IT tickets and request an engineer to the data. Thus, a lot of risks can be associated with this procedure. The process may become costly, slow and even offer inconsistent results.

With the help of a semantic layer, users can generate consistent reports from data sources; hence, the data can remain standardized, clean, and secured. Therefore, there are many ways in which a semantic layer can help an organization.