Building blocks of Data fabric architecture –

1.
1. Data management practice first defines stakeholders who can access business information; how much of it can be drilled down to detail, how often it would be updated, and details of what will be masked and encrypted and transformation efforts. Knowledge graphs and AI-powered metadata activation allow for unified data governance ensuring the safety and accuracy of organizational data.
2. Data ingestion enables users to connect to all types of business information regardless of its localization and volume allowing combining multiple data types. Video recordings from brick-and-mortar stores with online financial transactions as well as aggregate information in streams or batches in real-time too.
3. Data processing is a staging area for data across types and formats to be filtered for further usage.
4. Data orchestration cleanses, enriches, aggregates and reformats processed business information to meet the requirements of the target data repositories or the applicable software application.
5. Data discovery helps business and IT specialists to apply data for recognizing dependencies and identifying inaccuracies.
6. Data access delivers data to multiple downstream consumer applications or people, or the data marketplace, for business users.