Data consolidation after a merger

Combining two data estates after a deal means mapping duplicate masters, keeping finance reconciled and retiring systems on schedule. This page covers the constraints, the open-source platforms that fit and how a partner should scope the work.

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Why merger data consolidation is a different job from a normal pipeline build

Consolidating two data estates after a merger is a sequenced program of interim pipelines, reconciliation and system retirement, not a single pipeline build. Two warehouses, two customer masters and two product catalogs have to produce one set of numbers while the finance team still closes the books each month. Open-source orchestration with Apache Airflow or Dagster runs the interim flows and their schedules, and a metadata catalog such as OpenMetadata or DataHub records ownership, lineage and quality checks across both estates. That combination fits the job because the work is mostly about tracking what moves where and proving it, which is what a catalog and an auditable orchestrator are built to show.

The main constraint is time-boxed control obligations, not technology. A newly acquired business can usually be left out of the acquirer's internal control assessment for a limited period, but that exclusion has conditions, and the excluded business and its significance must be disclosed. Reporting controls over the consolidated numbers, including the IT general controls over program changes, computer operations and access to data, cannot wait for the migration to finish. Confirm with your external auditor and securities counsel which periods and disclosures apply to your entity, and map each interim pipeline to the control it supports before the first production run.

Start with three decisions: which system is the financial reporting source of truth for each domain during the transition, who approves changes to the interim pipelines, and what evidence the reconciliation produces each close. Those decisions set the order of work for master data mapping and retirement. If any of the acquired estate processes personal data or regulated records, also confirm where those flows may travel before anyone grants cross-company access, because access from another jurisdiction can itself be a transfer.

Which regulatory and control requirements shape the consolidation build

This table maps the regulatory and control requirements most likely to apply to a merged data estate against what each one means for the consolidation build. Read each row as a design input: the requirement, the build change it forces, and the evidence an assessor or supervisor will ask to see. Confirm applicability with counsel and your compliance lead, since many of these depend on listing status, sector and where data subjects and services sit.

RequirementWhat it means for the buildEvidence to prepare
SEC ICFR exclusion for an acquired businessExclusion is limited to one year from the acquisition date and one annual report, so acquired ledgers and reporting pipelines must be brought into scope of ITGCs within that windowDated acquisition timeline, list of excluded businesses, significance disclosure, and a plan showing when each interim pipeline enters the control scope
SEC Release 33-8810 IT general control areasInterim warehouse-to-warehouse pipelines that feed financial reports need controls over program development, program changes, computer operations and access to programs and dataChange approval records for DAGs, flows and mappings, job failure logs, and privileged access reviews for both legacy and target estates
Form 8-K Item 1.05 and third-party oversightConsolidation often adds vendors, contractors and offshore support, so the build must record which third parties can reach cybersecurity-relevant data and how incidents reach the disclosure committeeVendor inventory tied to pipelines, incident escalation runbook with a materiality decision path, and oversight notes for each service provider
NIS2 Article 3(4) notificationIf either company is an in-scope entity, changes to contact details, IP ranges, sector or service locations must reach the competent authority quickly, so the build should track network ranges and entity records as dataEntity register with IP ranges and Member State footprint, and a change process that flags updates to the authority within two weeks
DORA Article 28(3) ICT registerEach pipeline, orchestrator, connector and hosting arrangement supporting a financial function must appear in a register at entity and group level, including those inherited through the mergerRegister entries linking each platform and third party to the services and functions they support, kept current through the migration
DORA Article 28(8) exit strategies and transition plansDuplicate warehouses and legacy ETL tools that support critical functions need tested exit and transition paths before retirement, not just a decommissioning dateDocumented exit plan per retired system, data export tests, reconciliation results from parallel runs, and sign-off for each cutover
GDPR Articles 28 and 30 and EDPB Guidelines 05/2021Processing instructions for the merged estate must be documented, and remote access from a non-EEA acquirer's staff to EU personal data counts as a transfer, so access to target systems needs a transfer tool and restricted rolesUpdated records of processing covering both estates, processor instructions, transfer assessment for each non-EEA access path, and access logs showing who viewed EU personal data
HIPAA 45 CFR 164.314(a), where applicableIf the target handles ePHI as a business associate or covered entity, business associate terms must flow to subcontractors, and interim pipelines carrying ePHI need the Security Rule controls in placeExecuted business associate agreements, subcontractor flow-down terms, incident reporting path to the covered entity, and security controls documented for each pipeline

What data and systems each side of the merger brings

Customer data is usually the first domain where two companies collide. Both sides often hold the same legal entity under different internal IDs, with different name spellings, addresses, tax numbers and account hierarchies. Duplicates appear when one customer bought from both companies, when a CRM was migrated years ago, or when a sales team created records without a search step. Each side's warehouse may hold a golden record, a staging copy or only a snapshot from the CRM, and the answer changes the mapping work.

  • Duplicate keys: the same customer may appear under a CRM account ID on one side and an ERP customer number on the other, with no shared key.
  • Conflicting identifiers: tax registration numbers, DUNS-style identifiers or national company numbers may be missing, formatted differently or attached to the wrong entity.
  • Differing reference data: country codes, industry classifications, credit segments and sales territories often use different code lists.
  • Hierarchy differences: parent and subsidiary structures may be modeled differently, which affects consolidated revenue and credit exposure.
  • Target decision: the side with the more governed customer master usually becomes the target, but the choice should follow data quality evidence, not size.

Confirm which CRM, ERP and master data tools each side runs, and whether a warehouse such as ClickHouse sits on either side or only in the analytics layer.

Which open-source platforms fit a post-merger data estate and why

Consolidating two data estates usually needs four jobs done at once: moving data between warehouses, reconciling figures for reporting, mapping shared masters and retiring duplicates. The platforms below cover those jobs, but each carries a license, version or operating caveat that the integration team should settle before the first interim pipeline is built.

Apache Airflow for interim pipelines

Airflow schedules the interim extracts and loads between the two warehouses and gives the team one place to see run history, retries and failures. It is Apache-2.0 licensed and has no paid edition from the project itself. Airflow 2 reached end of life on April 22, 2026, so a new build should start on Airflow 3.x. Plan a PostgreSQL 14 to 18 metadata store from the outset, since SQLite is for testing only and a production deployment on it risks data loss.

Dagster for reconciliation jobs

Dagster models data as assets, so each reconciliation output, such as a revenue roll-up compared across both ledgers, can show which upstream tables it depends on. That asset lineage helps finance and the integration team trace a variance back to its source during close. Dagster is Apache-2.0 licensed. Confirm that the team is comfortable with asset-based authoring, since reconciliation logic written as ordinary Python tasks in Airflow may be easier to hand over to existing staff.

Airbyte for source connectors

Airbyte can pull records from the acquired company's SaaS tools and databases into a staging warehouse without custom connector code. The platform repository is licensed under the Elastic License 2.0, which restricts providing the software to third parties as a managed service. An internal integration team running it for its own use is a different question from a product offering, so confirm the license fit with counsel before adoption. Also check connector coverage for the acquired company's specific systems.

Apache NiFi for controlled transfer

When the two networks are separated by policy, for example during a period before identity and network integration, NiFi can move flows between zones through defined ingress and egress points with provenance records for each transfer. That provenance supports audit questions about what moved, when and by whom. Confirm the NiFi version, the cluster sizing for expected volumes and the team's experience with its flow governance, since flows built ad hoc during a merger tend to outlive the project.

OpenMetadata for lineage and quality

OpenMetadata covers table, column and pipeline lineage with OpenLineage event integration, plus data quality tests, profiling and ownership, which suits the work of mapping duplicate customer and product masters. It is Apache-2.0 licensed and lists more than 130 connectors. Collate maintains it and offers commercial enterprise capabilities and premium support. Version 2.0 changed several settings, including embedding credentials and the Python 3.12 ingestion images, so review the 2.0 release notes before upgrading an existing deployment.

DataHub as a catalog alternative

DataHub is an Apache-2.0 metadata platform that provides discovery, lineage and ownership across the combined estate, and it is a credible choice when the organization wants a catalog that its data engineers already know. Compare it with OpenMetadata on the connectors for both acquired systems, on the quality tooling the team needs and on the operating effort for its search and graph components. Choose one catalog, not both, to avoid two sources of truth for the same master data.

How a consolidation program moves from assessment to retirement

The sequence turns two unfamiliar data estates into one governed estate, with each phase producing evidence that finance, risk and auditors can check before the next phase starts. Nothing is switched off until the reconciliation and exit records say it is safe.

  1. Inventory systems and data flows

    The team lists every system that stores or moves customer, product, ledger and reporting data on both sides, including spreadsheets, scheduled jobs, reports and third-party feeds. Each system gets an owner, a data classification, the financial reporting processes it feeds and the controls around it. Owners of the target and acquired estates confirm the inventory line by line. The step is done when the inventory has no unowned systems and every flow into a financial report is traced to a named source.

  2. Map master data and define match rules

    Data engineers and business data owners compare customer and product records from both sides to find duplicates, conflicting identifiers and fields with different meanings. They write match and survivorship rules, document them in a shared glossary and record decisions in a catalog such as DataHub or OpenMetadata, where lineage and ownership can be kept. Sample sets are reviewed by business owners before rules are applied at scale. The step closes when each rule has an approver, a test set and a documented exception process.

  3. Build interim warehouse-to-warehouse pipelines

    Orchestrated pipelines, typically on self-hosted Airflow or Dagster, move data between the two warehouses so that combined reporting can run before systems are merged. Each DAG or asset is version controlled, reviewed by a second engineer and promoted through test and production environments under change approval. Schedules, retries, failure alerts and backfill procedures are written down for each job. The step is complete when pipeline runs, failures and reruns are logged and a sample of transformed records matches the source.

  4. Reconcile in parallel against finance tolerances

    For a defined period, both the legacy reports and the consolidated outputs run side by side. Finance and the controllers agree reconciliation tolerances for each report before the parallel run starts, and each difference is classified as explained, pending or defective. Results are kept as evidence with the query versions and run logs that produced them. The step is done when every reported figure is either within the agreed tolerance or has a documented explanation signed by the finance owner.

  5. Plan and execute the controlled cutover

    The cutover plan names the reporting processes that move, the rollback criteria, the order of changes and the people who approve each go or no-go decision. Access rights for the consolidated environment are reviewed, including any staff from the acquirer who gain access to target data, so that the access is granted on documented instructions and records of processing are updated. The cutover is complete when reporting runs from the target platform, the rollback path has been tested and the approvals are filed with the change records.

  6. Decommission duplicate systems and keep evidence

    Once the parallel run has been signed off and the cutover is stable, duplicate systems are archived, their data is retained or deleted according to the retention rules and the systems are shut down. Before shutdown, the team confirms that any regulatory exit or transition obligations that apply to the service are met, such as exit strategies for critical ICT services where the organization is subject to DORA. Evidence includes the final reconciliation, retention decisions, deletion certificates and updated system registers. The step is done when each retired system has a closed record that an auditor could follow from inventory to shutdown.

Deployment patterns when each company runs its own network and cloud

Before any pipeline is built, the two companies need an agreed layout for where orchestrators, catalogs and secrets live, because each choice decides who can reach which data. The four patterns below cover the common options and the checks that apply to each.

Shared orchestration plane in one tenant

One self-hosted Airflow deployment in a single tenant schedules jobs for both estates, with each company's source and warehouse connections defined as separate connections and scoped roles. This keeps scheduling, logs and failure handling in one place, which helps when finance needs one view of batch timing. Check that each company's connections are restricted to its own DAGs, and that the metadata database runs on PostgreSQL or MySQL, since SQLite is for testing only. Confirm the tenant's network path to both estates before agreeing on this layout.

Separate orchestrators bridged by a transfer layer

When each company must keep its orchestrator inside its own network, each estate runs its own instance and a controlled layer moves only the agreed extracts between them. This suits cases where one company's data cannot leave its zone before legal review is complete. The transfer layer needs logged, approved flows, and it is where intermediate files and credentials are most likely to be exposed, so review its access rules first. Ask whether the bridge flows are owned by the integration team or by each company's operations team.

Metadata catalog as a single view

A catalog such as OpenMetadata or DataHub can show both estates' tables, owners and lineage in one place while each source stays in its original network. The catalog holds metadata, so confirm that sample data, profiling output and lineage events do not copy personal or financial values into the shared view. Map duplicate customer and product masters in the catalog before pipelines reference them. OpenMetadata lists more than 130 connectors, so check each source type against its connector list.

Scheduler high availability and executor choice

Airflow can run more than one scheduler at once, using database row-level locks, which matters when a merged schedule must keep running during maintenance. Since Airflow 3.0.0, the hybrid CeleryKubernetesExecutor and LocalKubernetesExecutor are no longer supported, so the executor must be chosen from the current list before build. Confirm the scheduler count, the executor, and the database backup plan with the implementation partner in writing, because reconciliation jobs for financial reporting depend on them.

Credential and intermediate file placement

Credentials and staged files are where a merged data estate most often leaks data, because each company's secrets and temporary extracts may sit in the other's network. Decide, per flow, which secrets store holds each credential, which zone holds staging files, and how long those files are kept before deletion. Record every place a copy of EU personal data crosses a border, since remote access from a third country counts as a transfer. Ask the partner to show the placement map before any pipeline is connected.

What auditors and regulators will ask for and which component produces it

What does an ICFR scoping memo for an acquired business need to contain?

An ICFR scoping memo records which acquired business, data flows and systems management excludes from its internal control assessment, and why. The SEC staff allow exclusion of a newly acquired business, but not beyond one year from the acquisition date and not from more than one annual report, and the exclusion and its significance must be disclosed. The memo should list each in-scope financial data flow, its source and target systems, and the owner of each control over it. DeployOpen can prepare the system inventory, data flow diagrams and control mapping that feed the memo, but management owns the scoping decision and the disclosure. The SEC management ICFR FAQ is the primary reference to confirm the conditions with your auditors.

Which IT general control evidence do auditors need for pipeline changes and access?

Auditors look for evidence that changes to pipelines and access to data are authorized, tested and reviewed. The SEC guidance names program development, program changes, computer operations and access to programs and data as example IT general control areas, and management only needs to evaluate the controls that address financial reporting risks. For a self-hosted pipeline estate, the usual evidence is change tickets linked to merged pull requests for DAG and flow code, approval records for production deployments, role assignments in Airflow or Dagster, and access review exports. The change tickets are the system of record; Git history and the CI pipeline logs supplement them. DeployOpen can configure these trails and prepare them for review, but the control design and the testing conclusion belong to your team and your auditors.

Which component produces reconciliation logs and exception records?

The orchestrator run history produces the execution record, and the reconciliation job produces the comparison result. In Airflow, task instance history records each run, its start and end times, retries and failures, and the reconciliation task can write row counts, control totals and mismatched keys to a table or file that is retained with the run. Dagster records asset materializations and check results for the same purpose. Exception records should capture each unmatched customer or product key, the rule that flagged it, the reviewer and the resolution date. Keep the reconciliation outputs in the organization's own storage with a retention rule that matches your record policy. Confirm the retention period with your finance controllers and auditors before the first close cycle.

Can OpenMetadata lineage and catalog exports serve as audit evidence?

OpenMetadata lineage and catalog exports can show where a figure in a financial report came from, but they are evidence of the data flow design, not proof that every run behaved as documented. OpenMetadata supports table, column, dashboard, pipeline and metric lineage with OpenLineage event integration, along with ownership, glossaries, classifications and data quality tests. Export the lineage graph, owner assignments and test results at each reporting period and store them with the period's close package. Lineage captured from scheduled runs should be compared with the run history so the reader can see both the design and the observed execution. Confirm with your auditors which lineage level, such as column level, they expect for the reports in scope.

What does a DORA register of ICT and data flows need from a merged estate?

A DORA register must list all ICT service arrangements, and for an acquired business it should include every data flow and third-party service that touches the merged estate. DORA Article 28(3) requires financial entities to keep this register at entity, sub-consolidated and consolidated levels. Article 28(8) also requires tested exit strategies and transition plans for services that support critical or important functions, which matters when interim pipelines between two warehouses are retired. For each arrangement, record the provider, the data categories, the locations of processing, the functions supported and the exit plan. The register can be partly generated from the catalog and pipeline inventory, but the entity remains responsible for its completeness. DeployOpen can help build the inventory and the exit plan documentation, while the competent authority and the entity's governance determine what the register must contain.

How do records of processing change after a merger under GDPR?

Records of processing must be updated when the merged estate changes what personal data is processed, where it is stored and who can access it from outside the EEA. GDPR Article 30 requires these records to describe the purposes, categories, recipients, transfers and, where possible, the Article 32 security measures. When a non-EEA acquirer's staff can access an EU target's systems, remote access counts as a transfer under EDPB Guidelines 05/2021, which requires a Chapter V transfer tool. Each pipeline's source, destination, transformation step and access group should map to an entry in the record. Catalog classifications and lineage exports help keep these entries current, but the controller must approve the updated record. Confirm the processing instructions for any processor with your legal team, since GDPR Article 28(3)(a) requires processors to act on documented instructions.

Who issues the audit opinion on this evidence, and what does DeployOpen provide?

DeployOpen prepares the systems, controls and evidence that an assessment will examine, but independent auditors and certification bodies issue the opinions, attestations and certifications. In practice, DeployOpen configures Airflow run history, Dagster asset materializations, OpenMetadata lineage exports and change ticket integrations so they can be retrieved for review, and documents how each piece of evidence is produced. The auditor decides whether the evidence is sufficient for the controls in scope, and the registrant or regulated entity makes the disclosure or regulatory filing. Ask any implementation partner to name which evidence each deliverable produces and which party reviews it, and confirm the evidence list with your external auditor before the engagement is scoped in writing.

How long must these pipeline records be kept, and who sets that rule?

Retention periods come from your legal, regulatory and audit obligations, not from the orchestration tool. The platform can keep run history, logs and exports for as long as the storage budget and configuration allow, but the retention rule should be written by the data owner, legal team and auditors. Airflow's metadata database and log storage, Dagster's event storage and exported catalog snapshots each need an explicit retention setting and a backup plan. For records that may later support a regulatory or audit request, store exports in write-once or access-controlled storage in your own infrastructure. Confirm with your compliance team which records must be retained, for how long, and where they must be stored before the first run of the merged pipelines.

Where consolidation programs usually break and how to design around it

The most common failure is a reconciliation that ties in aggregate but not at the record level. Totals for revenue, receivables or headcount match after the interim pipeline runs, so the program is declared on track, while individual customers appear twice, get split across two ledgers, or drop out during a join on a key that differs between the two estates. Design the reconciliation around record-level matching with explicit exception queues: every unmatched key is logged, assigned an owner and closed with a reason code. Finance and the external auditor will ask how a figure was tied, so keep the matching rules, tolerances and sign-offs in version control. Confirm with your finance controllers which reports must reconcile before cutover, because a reconciliation that covers only the reports leadership watches leaves the ledger-level gaps untested. Duplicate master records create the second failure. When two customer or product masters are merged without written survivorship rules, the pipeline picks whichever source loaded last, and the choice silently changes names, tax identifiers, prices or consent flags. Decide, per attribute, which system is authoritative, what happens when both have values, and who approves overrides. Keep the original source keys in a crosswalk table so every surviving record can be traced back to both estates. This also matters for SOX IT general controls, where the SEC guidance on IT general controls covers program changes and access to data, and for any personal data subject to GDPR Article 5 principles on accuracy.

Orphaned pipelines are the third failure. Interim jobs built to bridge the two warehouses keep running after cutover because nobody owns their retirement, and they continue to write stale copies of customer data into reports that people still read. Build an inventory of every DAG, flow, connector and scheduled extract before cutover, with a named owner, a consuming report and a decommission date. In Airflow, for example, check which DAGs still have active schedules and which connection objects hold credentials for the retired system. Credentials left behind are often the larger risk than the data flow itself. The fourth failure is cross-border access granted to acquirer staff without a transfer mechanism. Engineers in a non-EEA parent often need read access to an EU target's systems to finish the migration, and remote access from a third country counts as a transfer under EDPB Guidelines 05/2021. Agree the transfer tool and the access scope with counsel before accounts are created, restrict access to pseudonymized or masked extracts where the work allows, and log every session. Confirm with your data protection officer whether the controller's documented instructions under GDPR Article 28(3)(a) cover this access.

How much effort, time and input does a merger data consolidation need

What drives the cost of consolidating data after a merger?

The cost is driven mainly by how many source systems and warehouses the two companies run, how many master-data conflicts exist between customer and product records, how deep the financial reconciliation must go, and how much of the estate falls in regulated scope. Each added system adds connector work, mapping rules and testing. Conflicting master records need business decisions on which attribute wins, which takes time from people who are not engineers. Reconciliation depth depends on how many ledgers, subledgers and reports must tie out for the close. Regulated scope adds evidence work for controls, change approval and access reviews. Ask the partner to show how each of these drivers maps to the line items in the quote.

Which parts of a merger data consolidation are one-time and which recur?

Discovery, source mapping, master-data matching, interim pipeline builds, reconciliation design and the retirement plan for duplicate systems are one-time work. Platform run costs recur: compute and storage for the orchestrator, warehouse and catalog, backups, upgrades, security patching and on-call coverage for failed jobs. Catalog upkeep also recurs, because lineage, ownership and glossary entries go stale when teams change. Open-source components carry no license fee for Apache Airflow, which is licensed under Apache-2.0 with no paid edition from the project itself, but the hosting and staffing costs still apply. Ask the quote to separate one-time delivery from annual run costs, with the run costs stated per component.

Can our internal team run a merger data consolidation without a partner?

Some organizations can, if they already run the orchestrator, warehouse and catalog in production and have engineers who know both source estates. The work is hard to do alone during a merger because the same people usually run the day-to-day close, handle integration decisions and support the acquired systems. Gaps typically appear in master-data decisions that need finance and business sign-off, in reconciliation evidence that auditors will ask for, and in on-call coverage for interim pipelines that must run until the old systems are retired. A useful self-assessment is to list the systems, name an owner for each, and check whether that owner has time for the next six months.

What does a merger data consolidation need from finance and IT?

Finance needs to name owners for the reconciliation rules, approve how conflicting customer and product records are resolved, and confirm which reports must tie out for the close and for external disclosure. IT needs to provide read access to source systems, network paths between the two estates, service accounts with least privilege, and a change process for the new pipelines and data models. Both teams need to agree on a single decision log, because master-data choices affect billing, reporting and access rights. Decisions that wait for weeks are often the main cause of schedule slip, not the technical build.

How long does a merger data consolidation take?

The duration depends on scope: the number of systems in each estate, how many master-data conflicts need business decisions, how deep the reconciliation must go, and whether regulated reporting depends on the consolidated data. No duration is fixed in advance. For financial reporting, the SEC allows management to exclude a newly acquired business from its assessment of internal control over financial reporting, but not beyond one year from the acquisition date and not from more than one annual report, and the exclusion and its significance must be disclosed. Use that window to plan the control work, and ask the partner to propose a timeline tied to written milestones.

What regulated scope changes the effort in a merger data consolidation?

Regulated scope adds evidence and control work on top of the technical build. For SEC registrants, IT general controls over program changes, computer operations and access to programs and data matter only where they support controls over financial reporting, so scoping that link early reduces effort. DORA requires financial entities to keep a register of ICT service arrangements and tested exit strategies for services supporting critical functions, which the consolidation plan may affect. Where personal data moves across borders, a non-EEA acquirer's staff accessing EU systems can count as a transfer that needs a transfer tool. Each of these adds review, legal input and documentation.

What should a written quote for merger data consolidation include?

A written quote should list the systems in scope for each estate, the deliverables for each phase, and the assumptions about master-data decisions, reconciliation depth and regulated controls. It should state who does each task, what the client team must provide and by when, and which items are fixed scope versus optional. Ask for the one-time delivery price separated from the recurring platform run, support and catalog upkeep, with the hosting assumptions stated. Require a retirement plan for duplicate systems as a deliverable, and ask how changes in scope are priced and approved. DeployOpen agrees scope, deliverables and timelines in writing before work starts and quotes from that written scope.

What should the team check before accepting a consolidation partner's estimate?

Check that the estimate starts from an inventory of both estates, not from a generic template. Ask how many source systems and warehouses are counted, how master-data conflicts are sized, and which reconciliation reports are covered. Ask which open-source orchestrator and metadata catalog the partner proposes and why, and whether the chosen versions are still supported. For Airflow, Airflow 2 entered end of life on April 22, 2026, so an estimate that builds on it needs a migration line. Confirm that the partner plans for backups, upgrades and on-call handover before the project closes.

How DeployOpen scopes and runs a consolidation program

DeployOpen plans, implements, integrates, documents and supports self-hosted open-source platforms inside the client's own infrastructure, so a consolidation program starts from the written scope and ends with systems and evidence the client operates. Engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work begins.

How we scope

  • Inventory both data estates, including customer and product masters, warehouses, pipelines and the reports that depend on them.
  • Define which interim pipelines, reconciliations and master-data mappings are in the written scope and which stay with the client.
  • Confirm regulatory boundaries early, such as cross-border access by an acquirer's staff and the evidence each reporting obligation needs.

How we build

  • Build interim pipelines between the two warehouses on self-hosted orchestration, with version-controlled jobs and tested failure handling.
  • Map duplicate customer and product records and document matching rules, exceptions and the owner who approves each decision.
  • Test reconciliations against agreed financial totals and record each variance so finance can trace it to a source.

How we hand over

  • Deliver a documented retirement plan for duplicate systems, sequenced by dependency and by the reports each system still feeds.
  • Hand over runbooks, data lineage records, access lists and reconciliation evidence in formats the client's own teams can maintain.
  • Train the client's operators on the platforms deployed in their infrastructure so the program does not depend on DeployOpen staff.

How we support

  • Offer ongoing support, upgrades and continuous testing as a retainer after the consolidation work is handed over.
  • Plan platform upgrades for the orchestrator, catalog and warehouse components so reporting pipelines keep running during the transition.
  • Confirm with the client which support scope, response expectations and review cadence apply before the retainer starts.

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