CRM migration

Migrate from Data Team DDS to Salesforce Sales Cloud

Field-level mapping, validation, and rollback between Data Team DDS and Salesforce Sales Cloud. We move data and schema; workflows are rebuilt natively in Salesforce Sales Cloud.

Data Team DDS logo

Data Team DDS

Source

Salesforce Sales Cloud

Destination

Salesforce Sales Cloud logo

Compatibility

92%

11 of 12

objects map 1:1 between Data Team DDS and Salesforce Sales Cloud.

Complexity

BStandard

Timeline

5–7 days

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Teams migrate to Salesforce Sales Cloud when their current CRM lacks the customization depth, reporting scale, or ecosystem integrations that enterprise-grade sales operations demand. Salesforce enforces a fundamentally different schema model than most source CRMs — a split between Leads and Contacts, record-type-keyed opportunity stages, and field-level security that gates visibility at the column level. The migration carries standard CRM objects (contacts, companies, deals, activities, custom objects) from Data Team DDS into Salesforce's record-type and page-layout model. The hardest problems are mapping source lifecycle or status fields to Salesforce's separate Lead and Contact objects, preserving association labels through Salesforce's sharing rules, and getting RecordTypeId assignment correct per deal type before field mapping can proceed cleanly. Automations, workflows, sequences, and email templates do not migrate — they must be rebuilt in Salesforce Flow or the appropriate automation tool, and FlitStack exports definitions as a rebuild reference. We sequence the migration so foreign keys resolve correctly (Accounts before Contacts, Contacts before Opportunities), run a representative sample with field-level diff before the full run, and capture any in-flight changes during cutover through a 24–48 hour delta-pickup window. We use Salesforce Bulk API for large record volumes and standard REST API for smaller datasets or complex field transformations.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

Data Team DDS logo

Data Team DDS

What's pushing teams away

  • Practices report that limited integrations with imaging systems and lab partners force manual workarounds that erode efficiency gains
  • Custom reporting capabilities are often described as insufficient for practices tracking production by provider or case type
  • Smaller practices cite pricing as a barrier when evaluating tier upgrades for multi-location or multi-doctor setups
  • User interface complexity for staff with limited technical experience creates onboarding friction, especially for front-desk teams new to the system

Choosing

Salesforce Sales Cloud logo

Salesforce Sales Cloud

What's pulling them in

  • The AppExchange marketplace with 5,000+ prebuilt apps gives enterprises integrations for nearly every business workflow without custom development.
  • Native Einstein AI for lead scoring, opportunity insights, and predictive forecasting adds intelligence without a separate platform purchase.
  • Territory management, multi-currency support, and advanced forecasting satisfy the needs of complex B2B sales organizations with structured revenue teams.
  • Slack, Tableau, and CPQ are deeply integrated into the core platform, keeping the sales stack unified for teams already in the Salesforce ecosystem.
  • Organizations with a large, established Salesforce implementation choose it because switching costs — integrations, custom code, trained admins — are prohibitive.

Object mapping

How Data Team DDS objects map to Salesforce Sales Cloud

Each row shows how a Data Team DDS object lands in Salesforce Sales Cloud, including any object-level transformations, lookup resolution, or schema-design dependencies.

Typical mapping — final map is confirmed during the sample migration step.

Data Team DDS

Contact

maps to

Salesforce Sales Cloud

Contact

1:1
Fully supported

Direct 1:1 map for contacts that route to the Contact object. Salesforce requires AccountId for most contact operations — contacts without a primary company in the source land on a default 'Unassigned' Account or are flagged for your admin to resolve before migration runs.

Data Team DDS

Contact (lifecycle-stage in [lead, mql, sql, customer, evangelist])

maps to

Salesforce Sales Cloud

Lead / Contact (split by final lifecycle value)

1:many
Fully supported

Contacts ending at 'Customer' or 'Evangelist' route to Salesforce Contact. All other lifecycle values route to Salesforce Lead. The split happens based on the final lifecycle value at migration time — stage-transition history is preserved as Lifecycle_Stage_History__c custom field for audit continuity.

Data Team DDS

Company

maps to

Salesforce Sales Cloud

Account

1:1
Fully supported

Direct map. HubSpot company hierarchies (parent/child) preserved using Salesforce's Parent Account field. Multi-company contacts collapse to one primary AccountId with Account Contact Relations for the rest — your admin chooses the primary-company selection rule before migration. If a contact is linked to more than one company, each additional company appears as an Account Contact Relationship, preserving the original association label and any related custom fields.

Data Team DDS

Deal

maps to

Salesforce Sales Cloud

Opportunity

1:1
Fully supported

Direct map. Each deal's pipeline maps to a Salesforce Sales Process tied to a record type. The deal's stage, amount, close date, and owner all migrate as Opportunity fields. Deal name becomes Opportunity Name, and deal amount maps directly to the Amount field.

Data Team DDS

Pipeline

maps to

Salesforce Sales Cloud

Sales Process + Record Type

1:1
Fully supported

HubSpot pipeline becomes a Salesforce Sales Process keyed by RecordTypeId. Each pipeline requires its own record type in Salesforce so that stage pick-list values and page layouts are scoped correctly per deal type. Your admin pre-creates record types before migration — we deliver the setup plan.

Data Team DDS

Pipeline Stage

maps to

Salesforce Sales Cloud

Opportunity Stage

1:1
Fully supported

Stage names map value-by-value per record type. Stage probability, forecast category, and stage-entered timestamps are re-applied based on Salesforce's stage model. We preserve the original stage-enter date as a custom datetime field so reporting continuity is maintained after go-live. During migration, each stage transition also records the Salesforce StageName that corresponds to the source stage name, ensuring that historical pipeline reporting reflects the same milestones.

Data Team DDS

Lifecycle Stage

maps to

Salesforce Sales Cloud

Custom field (Lifecycle_Stage__c) on Lead and Contact

1:1
Fully supported

Salesforce has no native lifecycle-stage equivalent. We migrate the field as a custom pick-list (Lifecycle_Stage__c) on both Lead and Contact. Stage-changed timestamps are preserved as Lifecycle_Stage_Updated__c custom datetime fields. Salesforce admins configure the pick-list values to match source values during schema setup.

Data Team DDS

Activity (call, email, meeting, note)

maps to

Salesforce Sales Cloud

Task / Event / Note

1:1
Fully supported

HubSpot calls and emails map to Salesforce Tasks with Type='Call' or Type='Email'. Meetings map to Events with original start/end times preserved. Notes map to Salesforce Notes (not legacy Note object). Original timestamps, owners, and parent-record links are preserved; activity-to-record associations are re-established in Salesforce.

Data Team DDS

Custom Object

maps to

Salesforce Sales Cloud

Custom Object

1:1
Fully supported

Custom objects map 1:1 to Salesforce custom objects. Custom object associations that use a HubSpot N:N model need Salesforce junction objects when the relationship is many-to-many — we surface this in the migration plan and your admin defines the junction object structure before migration.

Data Team DDS

Attachment / File

maps to

Salesforce Sales Cloud

Salesforce Files (ContentDocument / ContentVersion)

1:1
Fully supported

File attachments on records are re-uploaded to Salesforce Files. Salesforce's default file size limit is 25 MB per file — files exceeding this are flagged before migration so your team can decide whether to split, compress, or store externally. Inline images in notes are downloaded and rehosted in Salesforce.

Data Team DDS

Workflow / Automation

maps to

Salesforce Sales Cloud

Salesforce Flow

1:1
Fully supported

Workflows and automations are platform-native constructs that do not have a direct migration path to Salesforce. FlitStack exports workflow definitions as a rebuild reference document for your Salesforce admin. Automations must be rebuilt in Salesforce Flow — the exported definitions serve as the functional spec for the rebuild.

Data Team DDS

Report / Dashboard

maps to

Salesforce Sales Cloud

Report / Dashboard

1:1
Fully supported

Reports and dashboards are configuration artifacts that do not migrate. The underlying data that reports reference does migrate, so report bodies can be rebuilt on migrated data after go-live. FlitStack exports report and dashboard names and configurations as a reference list for your Salesforce admin.

Gotchas + challenges

What specifically takes care here

Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.

Data Team DDS logo

Data Team DDS gotchas

High

No publicly documented public API found in research

Medium

Custom field schema varies per practice account

Medium

Insurance payer mappings are state and plan-specific

Salesforce Sales Cloud logo

Salesforce Sales Cloud gotchas

High

Workflow Rules and Process Builder are retired

High

Bulk API batch quota exhaustion during large imports

Medium

Storage overage billing is non-obvious

Medium

Account-Contact many-to-many relationship mapping

Low

Territory and team member import ordering dependencies

Pair-specific challenges

  • Lifecycle stage one-way routing requires final-value split across Lead and Contact

    Data Team DDS lifecycle stage only moves forward by default — migrating historical records that ended at 'Customer' but passed through earlier stages requires Salesforce-side flexibility because Salesforce splits these into separate objects. We map each contact based on final lifecycle value: records ending at 'Customer' or 'Evangelist' land as Salesforce Contacts; everything else routes to Salesforce Leads. The original lifecycle history is preserved in a custom audit field (Lifecycle_Stage_History__c) so the transition path is visible in Salesforce even though stage progression cannot be replayed natively.

  • Pipeline-to-record-type 1:1 mapping creates schema-prep work before data lands

    Every Data Team DDS deal pipeline requires a corresponding Salesforce Record Type so that stage pick-list values are scoped correctly per deal type. Teams with five pipelines in the source system end up with five record types in Salesforce — each needing its own page layout, profile assignment, and validation rules. We deliver a record-type-and-page-layout setup plan as part of the migration so your Salesforce admin can pre-create the schema before validation runs. If record types are not set up before migration, field mapping cannot resolve correctly per pipeline.

  • N:N contact-to-company associations collapse to a primary AccountId plus relations

    Data Team DDS supports N:N contact-to-company associations natively, where a single contact can be associated with multiple companies simultaneously. Salesforce contacts have a single primary AccountId — everything else is an Account Contact Relationship. We migrate one primary company per contact (the most-recently-modified by default, or by your specified rule) and surface the rest as Account Contact Relationships. Your admin decides which company counts as primary before migration runs. The chosen primary company is stored as the AccountId on the Contact, while each additional association is added as an Account Contact Relation record, preserving the original relationship label and any associated custom properties.

  • Workflow and automation definitions have no migration path — rebuild required

    Automations built in Data Team DDS — including workflow rules, sequence enrollments, scoring rules, and notification triggers — are platform-native constructs that do not have a direct equivalent in Salesforce's schema. FlitStack exports workflow definitions as structured reference documents that your Salesforce admin can use as a functional spec when rebuilding in Flow. This is a manual step that requires Salesforce admin time post-migration and is not included in FlitStack's data-migration scope.

Migration approach

Six steps for a successful Data Team DDS to Salesforce Sales Cloud data migration

  1. Stand up Salesforce schema first

    Before any data moves, your Salesforce admin (or our team) creates the record types, page layouts, and custom fields needed for the migration. We deliver a schema setup plan based on your Data Team DDS pipeline count, custom property count, and lifecycle-stage configuration so the Salesforce side is ready before validation runs. If record types are missing, field mapping cannot scope per pipeline and data will land in the wrong stage pick-list.

  2. Resolve owners and users by email

    Salesforce users are matched against Data Team DDS owner IDs by email. Unmatched owners are flagged before migration — your team either invites them to Salesforce first or assigns their records to a fallback owner. No record lands in Salesforce without a valid OwnerId. This step also surfaces any archived or deactivated users in the source that may need special handling.

  3. Migrate accounts before contacts before opportunities

    Salesforce enforces a dependency chain: Accounts must exist before Contacts (via AccountId), and Contacts must exist before Opportunities (via Opportunity Contact Roles). We sequence the migration so foreign keys resolve correctly — Companies → Accounts first, then Contacts and Leads split by lifecycle stage, then Deals → Opportunities with stage and RecordTypeId mapping per pipeline. Custom objects and their junction relationships are sequenced based on the dependency graph your admin defines during planning.

  4. Run a sample migration with field-level diff

    Run a sample migration with field-level diff: A representative slice migrates first — typically 100–500 records spanning contacts, companies, deals, and a few activities. We generate a field-level diff between source and destination so you can verify lifecycle-stage routing, pipeline-to-record-type mapping, owner resolution, and file re-upload before the full run commits. Any mapping corrections happen at this stage, not during the production migration. The diff report highlights any missing field mappings and flags data quality issues, such as duplicate emails or invalid country codes, before the production run.

  5. Cut over with delta-pickup for in-flight records

    The full migration runs against Salesforce using Bulk API for large volumes. A delta-pickup window (typically 24–48 hours) captures any records created or modified in Data Team DDS during the cutover so Salesforce reflects the final state at go-live. Our audit log captures every operation, and one-click rollback is available if reconciliation fails. Your team continues working in Data Team DDS throughout — FlitStack uses scoped read access only.

Platform deep dives

Context on both ends of the pair

Data Team DDS logo

Data Team DDS

Source

Strengths

  • Specialized for dental practice workflows including scheduling, treatment planning, and insurance claim handling
  • Patient record management consolidates demographics, clinical history, and billing in one linked system
  • Appointment scheduling with provider assignment supports multi-chair and multi-provider practice configurations
  • Insurance claim tracking with payer reference and status monitoring reduces follow-up effort on rejected claims
  • Custom fields allow per-practice configuration for referral tracking, recall preferences, and specialty flags

Weaknesses

  • Reporting and analytics capabilities lag behind broader CRM platforms, limiting production and revenue-cycle insights
  • Integration ecosystem is narrower than horizontal CRMs, requiring custom work for specialty imaging, lab, or ERP connections
  • Custom field schema varies by practice, creating migration complexity when switching to a destination system with a different data model
  • Multi-location support is limited on lower tiers, restricting scalability for growing dental groups
  • Export mechanisms may require manual intervention or third-party tools, as no fully documented public API was found in the research
Salesforce Sales Cloud logo

Salesforce Sales Cloud

Destination

Strengths

  • Largest enterprise app ecosystem in CRM with 5,000+ AppExchange integrations covering nearly every vertical workflow.
  • Native Einstein AI delivers lead scoring, opportunity insights, and predictive forecasting without a third-party layer.
  • Advanced territory management, multi-currency, and flexible forecasting satisfy complex B2B revenue structures.
  • Deep platform extensibility: Custom Objects, Apex, Flow, and the Metadata API allow full schema customization.
  • Well-documented REST API, Bulk API, and Composite API with published rate limits for programmatic migration.

Weaknesses

  • Pricing model is layered and opaque in practice: per-seat fees plus storage overages, add-on subscriptions, and annual uplifts compound to 30–40% above sticker price.
  • Workflow Rules and Process Builder are deprecated, forcing all orgs onto Salesforce Flow — a migration task that catches many teams by surprise.
  • Steep administrative complexity: meaningful configuration requires a dedicated Salesforce admin or consultant.
  • API rate limits are edition-gated (100k/day base for Enterprise) and easily exhausted by large historical imports without throttling.
  • Data export is exportable via Data Loader but preserving relationship integrity across 30+ objects requires careful ETL sequencing.

Complexity grading

How hard is this migration?

Standard CRM migration. 2 of 8 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Data Team DDS and Salesforce Sales Cloud.

  • Object compatibility

    B

    2 of 8 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    8-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    Data Team DDS: Not publicly documented.

  • Data volume sensitivity

    B

    Data Team DDS doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Data Team DDS to Salesforce Sales Cloud migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about Data Team DDS to Salesforce Sales Cloud data migrations

Answers to the questions buyers ask most during Data Team DDS to Salesforce Sales Cloud migration scoping. Not seeing yours? Book a call.

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Book a free 30 minute consultation

Most Data Team DDS to Salesforce migrations complete in 5–7 days for under 50,000 records with standard CRM objects. Mid-market setups with moderate custom fields extend to 3–6 weeks. Enterprise-scale migrations with heavy custom-object usage, multiple deal pipelines, or complex record-type setups can take 2–6 months. Mapping pipelines to Salesforce record types is the longest planning step and the one most likely to extend timelines if schema is not pre-prepared.

Adjacent paths

Related migrations to explore

Ready when you are

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