Historian Migration Runbook: Moving Tags, Archives and Interfaces Without Losing Data

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Historian data is often the only record of what happened in the plant, and it is used by engineers, quality, MES, reports and analytics. A migration must avoid gaps, duplicated data, broken reports and lost context. This template covers moves to new hardware, new versions or a different historian product; follow the vendor’s migration tools and documentation for product-specific steps.

Historian Migration Runbook: Scope & inventory, Data strategy, Build & test, Cutover, Validate, Rollback ready
Plan data, cutover and validation before touching production collectors.

Background: Industrial Historians Explained.

1. Purpose and scope

Move historian data collection, storage and access to the target system while keeping continuous data, historical archives and all consumers working.

In scope: collectors/interfaces, tag configuration, archives, asset models and calculations, event frames, displays and reports, consumers (SCADA trends, MES, BI tools, analytics), security and backups.

2. Prerequisites

  • Inventory: tags (count, types, compression settings), collectors and sources, archive sizes and date ranges, asset models, calculations, consumers and their connections
  • Decision on historical data: migrate all, migrate a period, or keep the old system read-only
  • Target sizing (storage, licences, performance) and vendor compatibility checks
  • Backups of the current historian. See OT Backup and Restore Runbook
  • Test and acceptance criteria agreed with data users (engineering, quality, MES, analytics)

3. Data strategy options

Option Description Consider
Full archive migration All history moved to the target Time and tool support for large archives; validation effort
Partial migration Recent years moved; older kept read-only or exported Consumers must know where older data is
No migration New historian starts fresh; old kept read-only Simplest; users need access to both

Regulated data (for example GMP records) must remain available and unchanged for its retention period; plan validation accordingly.

4. Risks and mitigation

Risk Mitigation
Data gaps during switchover Collector buffering (store-and-forward); overlap period collecting to both
Changed tag names break consumers Keep tag names or provide a mapping; update consumers in a controlled way
Different compression changes results Match or deliberately review compression and exception settings
Time zone or timestamp shifts Verify UTC handling and daylight saving behaviour
Loss of context (asset models, events) Migrate or rebuild models and calculations; test outputs
Duplicate data after backfill Control backfill windows; verify no double values

5. Execution

Historian Migration Phases: A: Build, B: Parallel collection, C: Migrate history, D: Consumer cutover
Parallel collection gives a comparison baseline and a rollback path.

Phase A: Build

  1. Install and harden target servers; configure security, backups and time synchronisation.
  2. Create tag configuration (import from the old system with mapping).
  3. Rebuild or migrate asset models, calculations and event definitions.

Phase B: Parallel collection

  1. Configure collectors (or new collectors) to send data to the target, with buffering enabled.
  2. Run in parallel for an agreed period (for example several weeks).
  3. Compare values and statistics for representative tags (raw, interpolated, averages) between systems.

Phase C: Historical data migration

  1. Migrate archives according to the chosen strategy using vendor tools.
  2. Validate counts, date ranges and sample values.

Phase D: Consumer cutover

  1. Repoint SCADA trends, reports, MES interfaces, BI and analytics connections to the target.
  2. Verify each consumer with its owner.
  3. Stop collection to the old system after the agreed period; keep it read-only if required.

6. Validation

  • No gaps across the cutover period for critical tags (check buffer backfill)
  • Sample comparisons within agreed tolerance (raw and aggregated)
  • Asset models, calculations and events produce expected results
  • All consumers working; performance acceptable
  • Security roles and access verified
  • Backups of the new historian completed and restore tested

7. Rollback

Until consumers are fully cut over, keep the old historian collecting. Rollback means repointing consumers to the old system; data collected only by the target during the attempt can be backfilled later if needed.

8. Escalation and sign-off

  • Contacts: historian vendor support, OT lead, IT infrastructure, data owners (quality, MES, analytics)
  • Sign-off by data owners that their use cases work; update documentation, backup register and data retention records

Before you apply this in a plant: this article is for education. Always check the current edition of the relevant standards, the manufacturer's documentation for your exact product and version, and your site's procedures. Safety-related work needs qualified personnel. See our editorial policy.

Written by Bhargava Reddy Kapireddy

Bhargava has 16 years of hands-on experience with MES, SCADA, DCS, PLC and industrial data systems across power generation, oil and gas, pharmaceuticals and process manufacturing. He founded MFG Tech Hub to share practical, vendor-neutral automation knowledge.

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