Which method can the data engineering team use to determine differences between a new and previous version of a table in Delta Lake?

Using Delta Lake's built-in versioning and time travel functionality is an effective method for determining differences between a new and previous version of a table. Delta Lake automatically versions your data as changes are made, which means that every time a write operation occurs (like an upsert or delete), Delta Lake creates a new version of the table while keeping the older versions intact.

Time travel allows you to query the table as it existed at a previous point in time by specifying the version number or a timestamp. This capability is particularly useful for comparing two versions of the same table, as you can simply issue a SELECT statement against the specific version of the table you want to compare against the current version. Delta Lake handles the complexities of accessing different snapshots of data seamlessly, making this method both efficient and straightforward for the data engineering team.

The other options, while they may pertain to Delta Lake or data operations in a more general sense, do not inherently provide the same level of integration, ease, or clarity when comparing versions of a table directly. For instance, parsing the transaction log could give insights into the changes made, but it would require additional effort to reconstruct what those changes mean in terms of the data itself. Using Spark event logs focuses on logs pertinent to