Data Movement Topology captures the movement of data across endpoints that meets various topology property needs.

Analytics relies on a successful data foundation; it must be backed with the right data and processes.
Consumer demand for usable data has increased the need for data engineering. Data and analytics leaders can mature their data engineering practice by delivering data products, automating release processes, proving business value early, eliminating operations overhead and fostering collaboration.

Market trends around data integration tools enable organizations to access, integrate, transform, process and move data spanning various endpoints and across any infrastructure. It allows organizations to support various use cases, including data engineering, cloud data integration, operational data integration and data fabric.

Organizations move to the cloud for different reasons and require justification — especially when migrating from on-premises to the cloud.
A well-thought approach to migrating the data and analytics platform to the cloud can maximize cost savings and reduce the ability to take full advantage of the cloud services and service provider capabilities in cloud analytics deployments.