Every Google Cloud project carries three identifiers, and the Professional Data Engineer exam expects you to know which one to reach for in any given situation. The three are Project Name, Project ID, and Project Number. They look similar at a glance but they behave very differently, and mixing them up is one of those small mistakes that costs points on the exam and causes broken automation in real work.
I want to walk through each one, show what they look like, and explain when each one shows up on the exam.
The Project Name is the friendly label you see in the Cloud Console. Something like Analytics Project or Marketing Data Warehouse. It is human-readable, it can include spaces, and you can edit it whenever you want.
The key thing to remember is that the Project Name does not have to be globally unique. Two different organizations can both have a project called Analytics Project and Google Cloud does not care. The Name exists for humans to scan a list and figure out which project is which. It has no role in API calls, IAM bindings, or anything that talks to the platform programmatically.
On the Professional Data Engineer exam, if you see a question that pivots on a value being editable and not unique, that is the Project Name.
The Project ID is the one you will actually use in your day to day work. It looks like analytics-project-prod-4912. Lowercase, alphanumeric with hyphens, no spaces, often with a number on the end because the base name was already taken somewhere on the planet.
Three things to know about Project ID:
Any time you run something like this, the value after the flag is the Project ID, not the Project Name and not the Project Number:
gcloud config set project analytics-project-prod-4912
gcloud compute instances list --project=analytics-project-prod-4912
bq query --project_id=analytics-project-prod-4912 "SELECT 1"The immutability point matters more than people expect. If you pick a sloppy Project ID at creation time, you live with it forever. The only way to change it is to create a new project and migrate. For data engineering workloads where you have BigQuery datasets, Dataflow jobs, Pub/Sub topics, and Cloud Storage buckets all referencing that ID, migrating is genuinely painful.
The Project Number is a long numeric value Google assigns automatically. Something like 847193562410. You do not pick it, you cannot change it, and you rarely type it by hand.
Where the Project Number shows up is in the plumbing. Service account email addresses for the default service accounts use it. The Compute Engine default service account looks like 847193562410-compute@developer.gserviceaccount.com. The default App Engine and Cloud Build service accounts follow the same pattern with the Project Number as the prefix.
You also see Project Numbers in resource names for some IAM operations, in audit logs, and in cross-project references where Google Cloud internally resolves who owns what. If you have ever set up a Pub/Sub subscription that pushes to a service in another project and granted the subscriber role to the Pub/Sub service agent, that service agent email contains the Project Number, not the Project ID.
The Professional Data Engineer exam will not ask you to define these terms in isolation. It will bury the distinction inside a scenario. A few patterns I see come up:
None of these questions ever say which identifier are you using directly. The exam tests whether you reach for the right one when the question is framed around behavior.
When I prepare candidates, I tell them to think of it this way. The Name is for your eyes. The ID is for your fingers when you are typing commands. The Number is for Google Cloud's internal records and for the default service account emails that Google generates for you.
If you keep that triage in mind, every project identifier question on the Professional Data Engineer exam becomes a quick read. You see the scenario, you ask whether it is about human readability, programmatic access, or internal references, and the answer falls out.
One more practical note. When you create projects through Terraform or through the Resource Manager API, you supply the Project ID and optionally the Name. The Number comes back in the response, generated by Google. If you are building a multi-project data platform, capture the Project Number alongside the ID in your state so you have it ready when you need to grant cross-project IAM later.
My Professional Data Engineer course covers Resource Manager fundamentals including project identifiers, folders, organization policies, and how these structures flow into IAM bindings on the exam.
