Cognitive Assisted Data Integration The Cognitive Assisted Data Integration component focuses on the processes and environments that
deal with the capture, qualification, processing, and movement of data in order to prepare it for storage
in the Analytical Data Lake repositories, which is subsequently shared with the Discovery & Exploration
and Actionable Insights components, via the Data Access component. The Data Ingestion & Integration
component may process data in scheduled batch intervals or in near real-time/”just-in-time” intervals,
depending on the nature of the data and the business purpose for its use. Various cognitive technologies
such as machine learning and natural langurage processing can be leveraged to semi-automate the data
ingestion and integration process.
Data to be integrated can come from public network data sources, provider cloud SaaS applications,
enterprise data sources, or streaming computing results. The results from data integration can be
passed to data repositories for analytical processing, or passed to enterprise data for storage or feeding
into enterprise applications.
Capabilities required for data integration include:
•
Batch Ingestion : This capability can be leveraged to ingest and prepare
structured or unstructured data in batch mode, either on-demand or at
scheduled intervals. The capability includes standard Extract, Transform
and Load (ETL) and Extract, Load and Transform (ELT) paradigms, in
addition to manual data preparation and movement.
•
Change Data Capture: This capability can be leveraged for replicating data
in near real time to support data migrations, application consolidation,
data synchronization, dynamic warehousing, master data management
(MDM), business analytics and data quality processes.
•
Document Interpretation & Classification: This capability streamlines
the capture, recognition, and classification of business documents, to