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Administration · Lesson

Import sets & transform maps

Quick answer

Import sets are the standard way to load external data into ServiceNow, a spreadsheet of users, a feed of assets, a nightly JDBC pull, and map it onto the right target table without corrupting your clean data.

Key takeaways

  • The pipeline
  • Coalesce, insert vs update
  • Transform scripts and field maps
  • Scheduling recurring loads
  • Common mistakes

Import sets are the standard way to load external data into ServiceNow, a spreadsheet of users, a feed of assets, a nightly JDBC pull, and map it onto the right target table without corrupting your clean data. The key idea is a two-stage pipeline: land raw data in staging, then transform it into the target.

The pipeline

Data source Import Set table Transform Map Target table (file / JDBC / REST) --> u_imp_xyz (staging) --> field maps + scripts --> sys_user raw, messy coalesce, convert clean

Raw rows land in a staging table first, so bad or malformed source data never touches your target directly. A transform map then copies each staging column into the correct target field, applying conversions and reference lookups.

Coalesce, insert vs update

A field marked coalesce is the match key. On each row, ServiceNow looks for a target record with the same coalesce value:

coalesce on email: match found --> UPDATE the existing user no match --> INSERT a new user no coalesce field --> every import INSERTs --> duplicates

You can coalesce on multiple fields (all must match), e.g. first_name + last_name + employee_number.

Transform scripts and field maps

Simple columns map field-to-field. For the rest, use transform scripts:

onBefore
Clean/enrich a row before it writes, split a name, look up a reference. Set ignore = true to skip.
onAfter
Act once the target row is written, create related records.
onStart / onComplete
Run once per import run.
Field map (script)
Compute a single target field from source columns.
Reference fields need care: a source value like a department name must resolve to a sys_id. Use a coalesce/reference lookup in the field map, or the reference will silently import empty.

Scheduling recurring loads

A Scheduled Data Import (a scheduled job) can run a file or JDBC import on a cadence, the standard pattern for nightly HR or asset feeds.

Common mistakes

  • No coalesce field, so every import inserts duplicates.
  • Mapping a reference to a display value that doesn't resolve, leaving it empty.
  • Transforming straight into production without checking the import log/rejects first.
  • Loading huge files in one transaction instead of batching.

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Check your understanding

  1. Imported data first lands in a...

    • A. Staging import set table
    • B. Production table directly
    • C. PDF
    Show answer

    A. Staging import set table

    Data stages first, then transforms into the target.

  2. What maps source columns to a real table?

    • A. A transform map
    • B. A business rule
    • C. An ACL
    Show answer

    A. A transform map

    Transform maps define the field mapping.

  3. To update existing records instead of inserting, use a...

    • A. Coalesce field
    • B. New role
    • C. Dashboard
    Show answer

    A. Coalesce field

    Coalesce matches incoming rows to existing records.

Frequently asked questions

What does the term Import sets & transform maps refer to in ServiceNow?

Import sets are the standard way to load external data into ServiceNow, a spreadsheet of users, a feed of assets, a nightly JDBC pull, and map it onto the right target table without corrupting your clean data.

What is worth remembering about Import sets & transform maps in practice?

Raw rows land in a staging table first, so bad or malformed source data never touches your target directly.

What is another point to note about Import sets & transform maps?

A transform map then copies each staging column into the correct target field, applying conversions and reference lookups.

What tends to go wrong with Import sets & transform maps?

No coalesce field, so every import inserts duplicates. Mapping a reference to a display value that doesn't resolve, leaving it empty. Transforming straight into production without checking the import log/rejects first.
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