Designing Teradata Semantic for BI Tools

Data Modeling

Designing Teradata Semantic for BI Tools

What is a semantic layer data warehouse?

A semantic layer is a business representation of corporate data that helps end users access data autonomously using common business terms. A semantic layer maps complex data into familiar business terms such as product, customer, or revenue to offer a unified, consolidated view of data across the organization.


What is the meaning of data semantics?

Semantic data is the information that allows machines to understand the meaning of information. It describes the technologies and methods that convey the meaning of the information. This term was created by Sir Tim Berners-Lee.


Semantic data elements are deceptively similar to the entities and attributes we find in a logical or physical data model. They are things like “customer,” “product,” “credit limit,” “net sales,” and so forth. What the semantic modeler must address however, is the context of the term-the data element- and how it relates to the data elements as present in the computing systems data stores. For example, is a customer an individual-the Purchasing Agent- or a company? Must a customer have actually purchased a product, or can a customer also be someone who is in the market for a (the) product? What in some contexts might be called a “prospect” might be called a “customer” in others. Is a customer a wholesaler or is the end consumer the customer? Is the wholesaler’s customer also called a customer?

The prototyping process brings together a customer’s business and IT subject-matter experts with the Teradata design team to define, test and confirm the business rules using representative data extracted from the customer’s system. This is done by applying the virtual physical data model (PDM) technique from a “view” built on the source data, which gets loaded as-is into the Teradata platform.

Once the PDMs are defined, the next step of building and defining transformation rules requires following a course of deliverables, such as data mapping, business rules capture and the data transformation definitions.


Reasons to Use a Semantic Layer

Semantic layers deliver a number of benefits, including the following:

  • Firstly, an ad hoc query environment that uses a semantic layer allows developers and analysts to work interactively with business users to prototype the reports that are needed. This can be immensely valuable.
  • Secondly, the presence of a semantic layer simplifies the creation of queries and increases productivity, accuracy and consistency between reports. This is clearly of benefit to all users who wish to create reports, not just business users.
  • Thirdly, knowledge of the mappings between business fields and database fields resides in the semantic layer, not in the heads of developers. This makes it much easier for developers to understand and maintain reports that have been created by others.
  • Finally, and perhaps most importantly, a semantic layer removes the dependency between queries and the data store. This is because queries that are built using a semantic layer are constructed (and stored) as sets of business fields and pre-defined conditions rather than as statements in the query language. Consequently, a change to the data store can often be handled globally, without the need to modify individual reports. If you’ve ever had to modify the SQL within hundreds of reports to accommodate a database design change, or had to change reports to take data from a different source you’ll know what a benefit this is!

Wrapping It Up:

There are real benefits to be gained through the use of semantic layers. Semantic layers are increasingly becoming available within all types of reporting environments, and their use should be encouraged. ollaboration between business and IT is central to the success of an EDW. Working in conjunction with the Teradata design team to prototype the business rules, correctly identify the data needed and define a data model to support the organization’s needs ensures quality business results.

Is there any quries on designing teradata semantic for BI tools & layers?