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Bigger Data & Semantic Layers

Bigger Data & Semantic Layers

As the world's data proliferates, semantic Layers are increasingly important and increasingly difficult to deliver and maintain.

A semantic layer is a business representation of data that offers a unified and consolidated view of data across an organization. It attempts to define the relationships between various data attributes and enable a unified business view that can be used for querying and deriving insights quickly and cost-effectively

The term "Semantic Layer" is a source of much confusion in data and analytics. Leaders may say things like "We need to define a semantic layer for our enterprise data". Others may argue that it already exists. Or that it will be too expensive.

Organizations struggle to arrive at a simple clear definition of what a semantic layer is much less how to enable it. Firms that do invest in semantic layer tools or solutions often find themselves saddled with expensive solutions that are underutilized and don't address the enterprise's most pressing concerns.

A key part of the problem stems from the fact that semantic layers mean different things to different people, depending on the context of their work.

To help with understanding the different ways semantic layers are conceptualized, here is a recommended reading list that covers Semantic Layers in the different contexts they are often used.

Data management:

Business intelligence and analytics:

Search engines:

Web development:

Software development: