Yes, you are correct. Data Orchestration is indeed the broader concept of managing data workflows and processes within an organization's data ecosystem. It encompasses the coordination, automation, and management of various data-related tasks and processes to ensure the smooth and efficient flow of data.

Data Orchestration involves activities such as data ingestion, data transformation, data integration, data quality checks, data enrichment, data routing, and data delivery. It encompasses the end-to-end management of data workflows, from the initial data acquisition to the final data consumption or analysis.

The goal of Data Orchestration is to enable organizations to effectively handle the complexity of their data landscape and ensure that data is available, reliable, and accessible to the right stakeholders at the right time. It aims to streamline data processes, improve data governance, enhance data quality, and optimize data-driven decision-making.

Data Orchestration often involves the use of various technologies, tools, and platforms to automate and manage data workflows. This can include data integration platforms, ETL (Extract, Transform, Load) tools, workflow management systems, data pipelines, and data orchestration frameworks.

By implementing Data Orchestration practices, organizations can achieve better data management, increased operational efficiency, improved data consistency, and enhanced data-driven insights. It enables organizations to harness the full potential of their data assets and drive business value through effective data management and utilization.