Orchestrating data pipelines
Data orchestration refers to the automated and coordinated management of data workflows across various stages of the analytics life cycle. This process involves integrating, cleansing, transforming, and moving data from diverse sources to a data warehouse, where it can be readily accessed and analyzed for insights.
We have already covered how dbt empowers data engineers and data analysts to move away from repetitive stored procedures and employ version control and testing found in traditional software engineering to help run data workflows. dbt is largely used for the transformation part of the analytics workflow.
On the other hand, the goal of data orchestration in analytics engineering is to streamline the flow of data through different tools and processes, ensuring that it is accurate, timely, and in the right format for analysis. This involves scheduling dbt jobs in the correct sequence – for example, managing dependencies between tasks...
