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SAP Practice

SAP Data Migration

Data quietly decides whether an SAP program succeeds. We plan and execute data migration with profiling, cleansing, transformation and reconciliation so that the data entering your new SAP system is accurate, complete and trusted from the first live transaction.

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Migrate master and transactional data into SAP with quality, controls and reconciliation that protect go live.

The business challenge

Legacy data is almost always worse than teams expect. Duplicates, missing fields, inconsistent codes and records no one owns surface late in the project, forcing rushed cleansing that competes with testing for the same scarce time before go live.

Migration is also frequently underestimated as a technical copy exercise rather than a business data quality program. Without clear ownership, defined rules and reconciliation, the new system goes live with flawed data, and the resulting errors erode confidence in the whole implementation.

Our approach

We treat migration as a governed program with business ownership. Early profiling exposes the true state of the data, cleansing is prioritized by impact and clear rules define what migrates, what is transformed and what is archived rather than carried forward.

We build a repeatable migration process with reconciliation at every stage, using proven SAP migration tooling. Each load is validated against source and against business rules, and mock runs rehearse the full cutover so the production migration holds no surprises.

Capabilities

  • Data profiling and quality assessment
  • Cleansing and enrichment with business ownership
  • Mapping, transformation and migration rules
  • Master and transactional data loads
  • Reconciliation and validation controls
  • Mock migrations and cutover rehearsal

How we deliver

  1. 01

    Profile

    Analyze legacy data to reveal its true quality, gaps and ownership.

  2. 02

    Define

    Agree scope, rules and what to migrate, transform or archive.

  3. 03

    Build

    Develop mappings and migration objects with validation built in.

  4. 04

    Rehearse

    Run mock migrations, reconcile results and refine the process.

  5. 05

    Execute

    Perform the production migration within cutover and confirm reconciliation.

Typical use cases

  • Migrating master data into a new SAP S/4HANA system
  • Cleansing duplicate and incomplete legacy records
  • Defining what history to carry forward or archive
  • Reconciling migrated balances to source systems
  • Rehearsing cutover through mock migrations
  • Establishing ongoing master data governance

Business impact

  • Accurate, complete data from the first transaction
  • Reduced go live risk and post go live errors
  • Clear business ownership of data quality
  • A repeatable, validated migration process
  • Confidence from thorough reconciliation
  • A clean foundation for reporting and operations

Frequently asked questions

Why does data migration cause so many problems?

Because legacy data is usually worse than expected and migration is underestimated. Early profiling and business ownership prevent late surprises.

What should we migrate versus archive?

We define clear rules by object and by history, carrying forward what the business needs and archiving the rest to keep the new system clean.

How do you ensure migrated data is correct?

We reconcile every load against source and business rules and rehearse the full cutover through mock migrations before production.

Who owns data cleansing?

The business owns data quality. We provide tools, profiling and process, but decisions on correct values rest with data owners.