Data Management
What you must understand
Data management in Boomi centers on profiles, maps, and documents. A JSON or XML profile defines structure; a flat file profile defines delimiters, qualifiers, and headers. Maps connect a source profile to a destination profile, and each mapping row can use functions, lookups, and conditional logic. Know simple versus complex maps, and how map functions differ from process-level scripting. Understand document caching, persistent versus non-persistent documents, and how document flow affects memory. Also know cross-reference tables and lookups for value translation, and data process shapes for deduplication and cleansing.
Traps that appear
Expect questions on map function behavior with null inputs, and on default values versus conditional mappings. A frequent trap is confusing profile options (such as optional versus required elements) with map validation. Another is assuming a lookup failure aborts the process; often it returns null unless you handle it. Watch for questions about flat file parsing with quoted delimiters and about JSON array handling when a single object arrives instead of an array.
Worked example
You receive orders as JSON and must write a flat file. The rule of thumb: normalize first, map second, format last. Create a JSON profile that tolerates optional fields, map to a flat file profile with explicit delimiters and a header row, and use a lookup to translate status codes. If the source sends one object instead of an array, use a conditional map or a data process shape to wrap it. Validate with a small sample before scaling.
Rule of thumb
Always test maps with null, empty, and unexpected-type inputs; most production defects appear at these edges.