🗃️ The Build Interface
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📄️ Organizing Your DAG
Learn how to organize your Directed Acyclic Graph (DAG) in Coalesce with our comprehensive guide. Discover techniques using graphs, subgraphs, and filters to build maintainable and scalable data pipelines. Improve visibility, enhance manageability, and boost productivity with our step-by-step instructions for creating efficient data workflows.
🗃️ Custom Node Types
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📄️ Multi Source Nodes
Multi Source nodes represent Coalesce's implementation of SQL UNIONs.
📄️ How To Refresh Node Data
Learn how to refresh your data pipelines
📄️ Bulk Editing
Coalesce supports bulk editing of columns in Column grid view and Node Editor.
📄️ Parsers
Coalesce's parsers analyze the structure of entries within a variant column and automatically generate columns and a JOIN that captures the different attributes within them.
📄️ Pre-SQL and Post-SQL
Discover how to leverage Pre‑SQL and Post‑SQL boxes in Coalesce to enhance your workflows. This guide explains how to create process logs, back up and audit supplier data, and run multiple SQL statements seamlessly—all while using able references like `ref_no_link` to ensure proper environment mapping without unnecessary dependencies.
🗃️ Data Quality Testing
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📄️ Column Lineage and Propagation
Coalesce includes a way to quickly view the lineage of each column as it is transformed throughout your nodes.
📄️ Advanced Node Functionality
When creating a connection, the user can specify a warehouse that should be used to refresh a job.
📄️ Column Transforms
Transforms are optional pieces of logic that can be applied to a column to either alter its data, or generate new separate data.
🗃️ Learn How to Build Your Pipeline
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