Frequently Asked Questions

Semantic SQL is simple to create SQL queries with no Joins or Union statements. The semantic SQL queries are formulated in standard SQL and  query the semantic business model (ontology) mapped to the data, instead of querying the data directly. It is also used to query Views created with the semantic model. Users benefit from a 360° view of data, graph traversals and semantic reasoning features, so SQL queries become easy to understand and query size is reduced significantly.

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

Timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Gartner describes the data fabric architecture as the means of supporting “frictionless access and sharing of data in a distributed network environment.” To make this architecture work, it is necessary to implement a means to understand and assembly heterogeneous data by providing it with business meaning and flexibly integrating sources of any structural type. This is challenging due to several reasons, starting from the constraints of the architectural alternatives, and ending with the complexity to understand and query the aggregated sources.

The available options haven’t changed much in the last decade: Consolidating data into a data warehouse or graph-structured database, federating reporting, and data federation. Each alternative introduces implementation and operational constraints that involve investments in infrastructure and maintenance and varied skill sets. Moreover, till now there hasn’t been an integrative solution that resolves both the architectural and the “last mile” usability challenges, that is, encapsulating the complexity of the solution so data consumers across the enterprise conveniently gain a 360° view of data and easily generate complex queries to deliver advanced analytics and reporting conveniently and fast.

Data virtualization solutions are a viable solution to this challenge but their use is costly because of the continuous maintenance required to maintain indexes and because of the lack of relationship-rich semantic capabilities which are key to reduce complexity for end users and speed up  analytics that make use of dynamic data sources.

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. Timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. Timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools, and can leverage existing data catalog solutions such as Collibra or Informatica.  Contact us to schedule a demo.

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. Timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
Timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why Timbr facilitates the fastest and most convenient implementation of digital twins.

Gartner describes the data fabric architecture as the means of supporting “frictionless access and sharing of data in a distributed network environment.” To make this architecture work, it is necessary to implement a means to understand and assembly heterogeneous data by providing it with business meaning and flexibly integrating sources of any structural type. This is challenging due to several reasons, starting from the constraints of the architectural alternatives, and ending with the complexity to understand and query the aggregated sources.

The available options haven’t changed much in the last decade: Consolidating data into a data warehouse or graph-structured database, federating reporting, and data federation. Each alternative introduces implementation and operational constraints that involve investments in infrastructure and maintenance and varied skill sets. Moreover, till now there hasn’t been an integrative solution that resolves both the architectural and the “last mile” usability challenges, that is, encapsulating the complexity of the solution so data consumers across the enterprise conveniently gain a 360° view of data and easily generate complex queries to deliver advanced analytics and reporting conveniently and fast.

Data virtualization solutions are a viable solution to this challenge but their use is costly because of the continuous maintenance required to maintain indexes and because of the lack of relationship-rich semantic capabilities which are key to reduce complexity for end users and speed up  analytics that make use of dynamic data sources.

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. Timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.