Data Catalog is the logical representation of the underlying Data Model, which is contextualized by the Metadata to enable a better understanding of the Data Model and the enterprise-wide data. For example, understanding the End of Period Book Balance in the context of Loans and Securities may require two definitions of the term in discovering. A further analysis of the Metadata helps discovering, the sources, current business uses of the element, validation checks, and any privacy aspects.
The Data Catalog comprises of elements called Business Terms supporting business needs of the Banking and Financial Services Industry across the Finance, Risk, and Regulatory Compliance Functions. Data Catalog includes sourced, calculated, and master elements. Elements that require conformation to the standards will have a list of expected values. A combination of Business Terms and Entities form the underlying Data Model. The search capability allows you to explore data by different dimensions.
The Data Catalog helps you understand the business relevance of an Element and the associated Data Definition, grain through Entities and Subject Areas. You can group the Data Catalog by Subject Area and this subset is narrowed down to a business use case (For example, Basel Credit Risk).
In a multi-domain Data Catalog environment, you need to select the required Financial Domain that filters the Subject Areas relevant to the selected Domain or Service, Entities under the Subject Area, and Elements mapped to the Entities.
The Data Catalog is the gateway to create, view, or manage the physical instance of the Data Model.
You can use out-of-the-box define Pipelines (table to table process, Connector) to load data into the Entity, and execute and manage the Process.
The fundamental objectives of the Data Catalog are as follows:
· To provide a unified logical view of the Enterprise Data Model.
· To enable data discovery using predefined Metadata that is modifiable by Users.
· To support end-to-end data lineage as it connects data sources and uses.
This Section provides information about the key capabilities of the Data Catalog.
Figure: Data Catalog Key Capabilities
Data Catalog provides the Data Model for the Financial Services Industry. The key capabilities of the Data Catalog are as follows:
· Catalog Browser: Data Catalog consists of a Viewing Framework. The Data Catalog Browser API-based Interface allows you to view the Data Catalog Components. The Catalog Browser enables the Users to go through the Data Catalog Contents and view the Business Terms by Domain, Subject Areas, and Entity. The Catalog Browser also shows the Properties of Business Terms, Contextual Definition in a User-friendly language, List of Vaues, Data Sourcing Components, and Data Quality Rules.
· In-built Data Modelling Capabilities: Data Catalog contains all the required information to establish services underlying the Data Model, which is Entities, Attributes, and the relationship between Entities and Attributes. Similar to any Entity Relationship Modelling Tool used for this purpose, the Data Catalog can build, manage and hold Data Model for the deployment purpose.
· Data Quality Checks Rule: Data Catalog Contents include Data Quality Checks Rule so the system incoming data can be verified and validated.
· Catalog Extension: Data Catalog supports a Framework to extend the Data Catalog called as the Data Catalog Extension or catalog Extension. The Catalog Extension allows user to extend the Seeded Catalog Contents to support a new or client-specific business use cases. You can add new Business Terms or customize the existing definitions when the Business Term is enforced by the external entities.
· Comprehensive Coverage: Data Catalog provides a collection of comprehensive Business Terms across the Business Lines and Use Cases .
· Data Movement: Data Catalog provides the mechanism of ‘Stage to Standardize to Process’ to move the Data along to the Result for analytical consumption. The Catalog Services are accessed through API calls used by the Data Services Module to move data.