Data Engineering is the best practices and technology capabilities to develop engineered data workflows and pipelines to and between operational and analytic data management infrastructures. Data Engineering includes the requirements and priorities for data orchestration, integration, and transformations including advanced analytics in the data engineering pipeline workflow.
Organizations use data engineering development and deployment capabilities to develop, debug, schedule, secure, govern and run data workflows for BI / analytic use cases. Deployments may be use-case specific, i.e., a small number of users doing data science projects with data sources / transformations required or may be required to be fault tolerant, highly secure, and scalable to span large data volumes, multiple analytic steps, multiple analytic models, and support multiple BI use cases and tools.
This report continues to explore market requirements and priorities for data orchestration, integration, and transformations including advanced analytics in the data engineering pipeline workflow.
We are confident that the insights in this report will be beneficial to your operations and strategic planning.
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