DevX Guide to Semantic Layers

DevX Guide to Semantic Layers

Quick Guide to Semantic Layers

The massive growth of the tech industry has greatly changed the way many businesses operate. Because of the massive prevalence of the internet and internet-based devices, there has been a massive spike in data usage. As such, data has become an extremely important and valuable commodity for all different kinds of businesses. With the innovation of the cloud, it has become much more feasible to monitor, track, and protect large amounts of data. The cloud enables people and businesses to turn data into valuable assets that can assist them in a number of different ways. In this article, we are going to take a look at semantic layers.

But what is a semantic layer? Why is a semantic layer important for businesses? What are a few benefits for businesses using semantic layers? Are there different forms of semantic layers?

Here is a quick guide to understanding semantic layers.

What is a Semantic Layer?

A semantic layer is essentially a consolidated representation of data across a business. Based inside the cloud, a semantic layer unifies a wide array of data from different sources into one manageable location. With semantic layers, businesses are able to read and analyze data that would otherwise be unreadable and useless to them. Semantic layers utilize software such as data warehouses to simplify data that would be otherwise complex and confusing. Typically semantic layers allow businesses to filter through larger pools of data using business-related keywords.

Why is a Semantic Layer Important for Businesses?

Modern technology has enabled businesses to collect massive amounts of data. When used properly this data can be used in analytics that helps drive future decision-making. However, the data collected often takes on multiple forms, formats, and definitions. With these differences, the data can become extremely difficult to make sense of as it is shared across departments or locations.

Semantic layers simplify this process. Semantic layers unify large pools of data into one singular, mapped-out entity. The semantic layer compresses otherwise complex data into understandable and easy-to-discern business terminology. This compression allows businesses to utilize data to meet their constantly growing analytics needs. It is important to note however, semantic layers do not actually store or hold the data. Instead, they rely on programs like data warehouses or data lakes to store the data. The semantic layer then acts as an abstract layer on top of these storage facilities which makes the data much more comprehensible and useful.

What are a Few Benefits for Businesses Using Semantic Layers?

  • Singular Unified Source of Information

With a semantic layer, data is compiled into one unified source of information. Anyone in the business, from any location, can access the same pool of data and discern the same information. Without a semantic layer, different departments may search for the same information and get different results. The semantic layer organizes data into a consistent unified mapping so that information stays consistent for everyone.

  • Improved Communication Across the Business

Because semantic layers compress large pools of data into a singular unified concept it enables much more fluent communication. Different departments can much more easily share important data or analytics findings.

  • Improved Performance and Reduced Cost of Resources

Because companies collect such large quantities of data, storing it all in on-site warehouses becomes extremely costly. It is also tough to scale the needed on-site storage as the company continues to grow. This leads to companies needing to shift to using cloud-based solutions. However, these cloud-based solutions can struggle performance-wise as the data is often messy and hard to interpret. Semantic layers allow the best of both worlds. Good semantic layers allow for easily-scalable and affordable cloud-based solutions that function at a high-performance level.

Are There Different Forms of Semantic Layers?

In short, yes, there are numerous different forms and styles of semantic layers. Here are a few different examples of different forms of semantic layers:

  • BI Tool-Based Semantic Models
  • Universal Semantic Layers
  • Data Warehouse-Based Semantic Layers
  • Semantic Layers Within Data Pipelines

Summary: A Quick Guide to Semantic Layers

Because of the massive growth of data and analytics, businesses have had to implement new cloud-based solutions to manage large quantities of information. Semantic layers unify these large and different forms of data into a singular, simplified thread of information. With semantic layers, businesses can much more efficiently manage, share, and utilize their data to drive analytics. If implemented correctly, semantic layers provide an easily scalable, cost-effective cloud solution. And unlike typical cloud solutions, semantic layers can run at an extremely high-performance level.

Semantic layers can be based in several different data storage solutions such as; data warehouses, data pipelines, and BI tools. Although they are somewhat of an abstract concept, when implemented correctly semantic layers make analyzing data much simpler. Regardless of the size of your business, implementing a semantic layer can be a huge benefit.


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