You think those are transformations? And how would you justify your answer there?

In an ETL pipeline, a transformation is any operation that changes the data’s structure, format, or content before it is loaded into the target system. Common examples include filtering rows, aggregating values, joining tables, converting data types, or deriving new columns. To justify that a step is a transformation, you can ask:

1. Does it modify the data in any way?
2. Is the output different from the input in structure or value?
3. Is it performed between extraction and loading?

If the answer is yes to these questions, the step qualifies as a transformation. For instance, converting a string date to a timestamp or calculating a total sales column from individual line items are classic transformations because they alter the data’s form or add derived information before it is stored.