Semantic SQL queries are no different in syntax than the standard SQL queries known to every data engineer, data scientist or analyst. However, despite the syntax being the same, Semantic SQL queries deliver a significant advantage: consumers benefit from a 360° view of data without JOINs, so query complexity is eliminated and time to value is dramatically reduced.
So how exactly does Timbr enable Semantic SQL?
Timbr enables users to create a virtual semantic business model that provides meaning to the endless datasets in an organization. The data is exposed using abstract or specific concepts representing internal business terminology, such as Customer, Revenue, Product, Transaction, etc. Concepts are then mapped to the underlying data stored in single or multiple sources. Concept mappings support functions and can include aggregated or filtered data. Users can use the concepts to define hierarchies and classifications of the data by using a no-code UI or writing the logic with SQL statements.
The secret sauce of Timbr’s semantic data models is the relationships. Relationships between datasets don’t exist in databases and can’t represent the contextual relation between two tables, nevertheless, between two business entities the data represents. Users can connect datasets once a relationship is defined using the explicit relation required in their scenario.
There are multiple types of relationships in the Timbr data model. There are one-to-many relationships, many-to-many relationships, and transitive (recursive) relationships. When leveraging these relationships in a query, behind the scenes, the Timbr platform translates the relationships into JOIN statements while optimizing the query and reducing the query length by up to 90% to allow any analyst to execute complex queries in a simple and elegant manner. Semantic relationships enable users to query the data model and provide a 360° view of data from any concept.
Once the model is ready, data consumers can connect and use the concepts as virtual tables, including the relationships, expose them to BI tools and Notebooks, or apply standard SQL to query the business concepts (thus Semantic SQL). Instead of manually creating the JOIN statements and applying the business logic every time they query the tables, users using the semantic business model can benefit from semantic reasoning features and graph capabilities that make SQL queries considerably less complex.
Read our blog that explains relationships in more detail.
Click here to learn how you too can benefit from Timbr’s unique Semantic SQL.
How do you make your data smart?
Timbr virtually transforms existing databases into semantic SQL knowledge graphs with inference and graph capabilities, so data consumers can deliver fast answers and unique insights with minimum effort.
