panaest.blogg.se - Ariba integration

The simplified view into your data created in the data preparation layer allows for consumers to easily understand the data in business terms. The Data Consumption layer enables the communication of data requests into Live Data Gateway and the serving of the requested data.

OLAP View – select a subset of existing measures and dimensions from an OLAP cube to create a view in APOS Live Data Gateway's Web UI.

Freehand SQL View – technical users can create a view based on SQL queries in APOS Live Data Gateway’s Web UI.

Semantic Layer View – non-technical users can select tables, fields and joins to create a view in APOS Live Data Gateway's Web UI.

Three types of data views can be utilized within the Data Preparation Layer: With these data complexities managed centrally, the end users of the semantic layer can quickly and easily build reports and visualizations, all while the strong data control and governance mechanism is protecting against inappropriate data access. Within the semantic layer, data views are created which define what data should be exposed, define measures and dimensions, manage data linking complexities, and rename data fields to meaningful business terms.

This semantic layer produces very strong benefits for both self-service analytics and self-service modelling. The Data Preparation Layer of Live Data Gateway enables important data transformation steps, and provides a simplified semantic layer for business users to easily navigate data and be shielded from the complexities of the underlying data structures. The primary connection protocol is JDBC, however connection via OData, XMLA, JSON, REST, and API is also supported. All connectivity is managed through this single virtualized data connection point, meaning that no database drivers or other connections mechanisms are required by any consuming application or user environment, instead Live Data Gateway manages all of these connection details. The Data Virtualization layer of Live Data Gateway is the connection point into the many data sources that are supported - Cloud Data, Relational Data, OLAP Data, Hadoop Data, Applications (On-Premise and Cloud). Live Data Connectivity & Data Consumption Methods Live Data Gateway Functional Layers: Data Virtualization Layer