In your current project, what is the source and what is the target? What type of data are you dealing with, and which ETL tools are you currently using? Is the source an external database or a print‑mix database? Which system is the target?

In an ETL pipeline the source is the system where the raw data originates, such as an operational database, a flat file, or an external API. The target is the destination where the transformed data is loaded, often a data warehouse, data lake, or a reporting database. The data type can range from structured relational tables to semi‑structured JSON or XML, or even unstructured logs. Common ETL tools include Informatica PowerCenter, Talend Open Studio, Microsoft SSIS, Apache NiFi, and cloud services like AWS Glue or Azure Data Factory. The choice depends on factors such as data volume, transformation complexity, real‑time requirements, and budget. For example, if the source is an external database and the target is a Snowflake data warehouse, you might use AWS Glue to extract data, perform transformations in Spark, and load into Snowflake. The pipeline typically includes extraction, transformation (cleaning, enrichment, aggregation), and loading steps, with monitoring and error handling built in.