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SIS and LMS data

The nightly extract is how most institutions give Unifuse their SIS and LMS data. Your registrar or IT team drops CSV files on an SFTP server each night; Unifuse picks them up, validates them and updates student records.

  • Add the Banner / LMS nightly extract (SFTP) connector under Integrations with the SFTP host, credentials and directory, the file-name patterns, and the email addresses to alert.
  • Agree the column layouts with Unifuse support during onboarding. Unifuse keeps the agreed column list for your institution so the registrar has a single reference.
FileDefault patternContent
Students*students*.csvOne row per student, in Banner column names (ID, name, term, GPA, standing and so on).
Registrations*registrations*.csvOne row per student per course section, with the course reference number.
LMS activity*activity*.csvPer student per section: current score; on-time, late and missing submissions; last activity.
LMS attendance*attendance*.csvPer student per section per date: status and minutes present.

Patterns match the file name only and ignore case, so dated file names need no change. Files load in the order above each night.

  • A file presented twice is ignored the second time; Unifuse matches on the file’s content.
  • Column order, letter case and surrounding whitespace do not matter. A renamed or missing column halts that file.
  • Malformed rows are quarantined and the rest of the file is imported. When a file has quarantined rows, the “mark missing students inactive” step is skipped for that night, so a bad file never deactivates students by accident.
  • A student missing from the students file is marked Inactive, never deleted. Notes, tags, escalations and caseload assignments survive.

When a file halts or rows are quarantined, Unifuse emails the alert recipients, writes a Critical entry in the audit log, and shows a red item in the notification bell for everyone with manage connectors.

Staged and quarantined rows are kept for 30 days and then purged. Batch summaries are kept.

The student record shows SIS and LMS data side by side, with Not on file wherever the latest import had nothing. The roster gains LMS Score and Attendance columns, and the nightly risk job uses the new data to place students in cohorts.