A business-friendly data format known as a semantic layer simplifies complex business logic. The term “business perspective” or “BI model” has been used to refer to business intelligence (BI).
The semantics describes a clear and understandable model of the data that allows for an easier understanding of the meaning of the data and how it should be used by analysts and other end users. It is the basis for building an enterprise information architecture that can support a wide range of business processes and enable better analytics and decision-making.
The semantic provides a high level of abstraction for describing information. The most common examples are Entity Relationship Diagrams (ERDs) which show relationships between entities such as customers and products; Data Flow Diagrams showing how data flows through a process; and Process Flows, showing how processes flow from one step to another.
Data lakes are a great way to store your data, but using them as a source of analysis is more difficult than it needed to be.
What if you could identify the customer key, ID, and date hierarchy without looking through each record? What if you could easily query all the records related to a specific customer?
That’s what Semantic Modelling does for your data lake: it makes it easier for you to use your data lake as a source of analysis.
Business users can create their semantic models using the latest BI technologies. the parameters, metrics, and hierarchies. But in this instance, obtaining a single source of truth is challenging. So that many teams may access their data using standard business terms, it is essential to have a common representation of the data.
To reach the goal being set, it is necessary to centralize the definition of your semantic models. This ensures that all teams can access the same information and work together effectively.
Consider a case with a large amount of complicated data, including billions of rows of data, millions of cardinalities, and hundreds of dimensions and metrics. Such data must be managed in a way that results in an easy-to-understand interpretation. This is where the semantic ordering comes in.
Semantic ordering provides a structure for organizing data in your enterprise so that you can query it more easily and efficiently. It’s a way to organize your data so that you can make sense of it and use it when it’s stored on multiple systems.
The semantic layer makes it possible to use familiar SQL commands from applications like Excel or SQL Server Management Studio (SSMS). You need not have to learn any new languages or tools; you just have to get comfortable thinking about your queries differently than before.
- Improves the data lake’s information and increases its utility for the company
- Makes it simpler for consumers to query large amounts of data on the cloud and local storage platforms
- Accelerates the speed of queries on large data
Semantic modeling will help you combine data from multiple sources, convert that data into a common format, and make it easier for you to work with. It will also help the different departments in your company work together rather than in silos. Semantic modeling is worth the time and effort, whether you use it as part of your BI strategy or create a data lake to improve your business process.