Adobe Campaign Classic Developer Expert study plan

Diagram the core Adobe Campaign tables (recipient, delivery, tracking log, subscription) and label every primary key, foreign key, and cardinality on the diagram.

Author three custom schemas from scratch: one extending the recipient schema, one standalone schema with its own auto-generated key, and one child table linked by a foreign key; validate all three with the schema editor consistency check.

Configure a 1-to-N link with an external join plus an aggregate-enabled collection, then write a short note justifying each cardinality and join choice.

Catalogue the automatic system fields (created, lastModified, createdBy, and their audit counterparts) and document which fields must be populated manually in an import.

Extend an out-of-the-box schema with two additional fields using the extension mechanism and confirm the change appears in the database structure without altering the original definition.

Define a shared enumeration and reference it from two different schemas, then show how its values appear in a query filter and in a personalization expression.

Add indexes to a custom schema and measure their effect on a filtered read against a large test table using the query execution plan.

Build a workflow that selects recipients with a Query activity, splits the population with a Split activity, and reunites the branches with a Union, checking row counts at every transition.

Insert a Deduplication activity and document the identification parameters and deduplication method chosen, along with why alternatives were rejected.

Add structured logging to the workflow so each run records input counts, output counts, and elapsed time.

Assemble an end-to-end nightly import workflow that loads a flat file through a data loading activity, enriches it with a lookup on an existing table, and writes results to a custom schema.

Add error handling to that workflow using a test activity on rejected lines, routing failures to a quarantine table rather than aborting the run.

Configure the workflow to restart safely after a simulated failure and prove that already-processed records are not duplicated.

Schedule the workflow as a recurring execution with a defined time window and verify the scheduler behaviour across two consecutive runs.

Refactor a duplicated sequence of activities into a reusable sub-workflow or a jump-based loop and explain the maintenance benefit.

Write ten SQL snippets for query activities covering joins, subqueries, aggregate functions, date arithmetic, and null handling, and record the expected result of each against known test data.

Compare an equivalent query built with the visual query editor against a hand-written SQL statement and note where the generated SQL diverges from what you would write.

Use a JavaScript activity to read the workflow target, loop over records, and write an audit line per record with correct use of instance variables and logging calls.

Query and update campaign data programmatically from JavaScript, then handle and log a failure case such as a missing record.

Measure the runtime of a JavaScript loop against a set-based SQL approach on the same data volume and document the performance gap.

Create three reusable personalization blocks and reference them from at least two different delivery templates.

Build conditional content that renders different blocks for three audience segments, and verify each variant using preview with different target profiles.

Configure a delivery template with routing, a seed address list, and proof recipients, then send and inspect a proof to confirm the configuration works end to end.

Set up an A/B split on a delivery with a defined winning criterion and interpret the resulting report to declare a winner.

Document the expression syntax and functions used in the personalization blocks so a non-developer could maintain them.

Authenticate to the SOAP API, run a query on the recipient schema, and create a new recipient programmatically, logging the response for each call.

Export the custom schemas and workflows built in weeks 1 to 3 into a package and import it into a second environment, resolving at least one naming or data-schema conflict.

Configure an external account for outbound routing or file transfer and prove connectivity with a test operation.

Automate a data exchange with an external system using a scheduled workflow and an imported file, validating records arrive with correct field mapping.

Compare API versus workflow-based integration for the same use case and record the trade-offs in latency, error handling, and maintenance.

Configure operator groups, named rights, and a security zone so that one test operator can read but not edit a custom schema, then verify the restriction by logging in as that operator.

Create three typology rules (a pressure rule, a control rule, and a filtering rule), attach them to a delivery template, and confirm each rule fires or excludes as intended.

Document how quarantine, seed addresses, and the audit log interact when a delivery is paused or a message is rejected.

Build a two-page web application with a form that prefills data from a query string, validates input, and stores the submission in a custom schema.

Add a confirmation page and error page to the web application and test both paths with deliberately invalid input.

Complete two full-length timed practice exams under exam conditions and score each by domain to identify the three weakest areas.

Re-run the labs from weeks 1, 3, and 6 from memory without notes to confirm retention of schema, workflow, and integration mechanics.

Build a one-page remediation plan for every question missed twice, citing the specific concept and the lab that reinforces it.

Recite the data model relationships, typology rule types, and API authentication flow from memory in a written summary.