Sizing a Salesforce Marketing Cloud Next migration starts with a data extension inventory. Marketing Cloud Next runs on Data 360 (formerly Data Cloud) and doesn’t support SSJS, so teams must classify what maps, what needs rebuilding, and what can be retired. Schema Explorer’s readiness workspace automates this first pass. 

The challenge goes beyond moving data from one platform to another. 

Marketing Cloud Next runs on Data 360, using data lake objects (DLOs) and data model objects (DMOs), and doesn’t support AMPscript or SSJS in the same way MCE does. Before teams can estimate migration effort, they need to understand what each data extension supports, what can map to the new environment, what needs to be rebuilt and what can be retired.

We used Marketing Cloud Schema Explorer to assess how much of this initial migration assessment a tool could help automate. 

Note: All screenshots in this post use dummy data from a demo account.

What is the Marketing Cloud Next readiness assessment in Schema Explorer?

The MC Next Readiness workspace is a planning layer that looks at your current MCE business unit and sorts it by likely destination in Marketing Cloud Next. In its own words, it helps you “classify data extensions, inspect migration evidence, and review likely MC Next landing zones before you plan the move.” 

Figure 1:  The MC Next Readiness workspace

A data extension (DE) is a table used to store and organize records and fields in Marketing Cloud Engagement. The workspace works at three levels: 

• A readiness summary for the whole business unit 
• A classification engine that groups every data extension by the role it plays today
• A record-level list showing each data extension’s status, suggested DMO target and supporting evidence 

An Export migration plan option gives the team a document to take into planning workshops.

What the readiness scan does—and doesn’t—cover

The readiness workspace tells you how ready you are from a data extension point of view: what your data looks like, and where it is likely to land in Data 360.

But data is only one part of a Marketing Cloud Engagement account.  

A complete move to Marketing Cloud Next also needs an audit of everything that uses that data, because most of it has to be rebuilt rather than migrated. 

Area	What to audit	Why it matters for MC Next
Emails and templates	Content Builder emails, templates, content blocks and dynamic content	Content doesn’t migrate automatically, and anything personalized needs reworking
AMPscript and SSJS	Scripting inside emails, content blocks, CloudPages and Script Activities	MC Next runs few of the functions of AMPscript but not SSJS, so this logic must be re-engineered
CloudPages	Landing pages, preference centres, forms and code resources	Often heavy on scripting and DE writes; each one needs a new home and design
Journeys	Entry sources, decision splits, wait logic, activities and goals	Entry and orchestration patterns change; journeys are rebuilt, not copied
Automations	SQL queries, script activities, imports, extracts and file transfers	SQL logic typically moves to Data 360 transformations, calculated insights or Flow
Integrations	Installed packages, API users and external systems calling MCE	Every connection must be repointed or rebuilt for the new platform
Subscribers and consent	All Subscribers, lists, publication lists and preference data	Consent must land correctly before a single email is sent from MC Next

In other words, the readiness scan is an excellent starting point for the data workstream, but it should sit alongside content, code, journey and integration audits to give the full picture of what a migration involves.

What the scan found across 1,862 Marketing Cloud data extensions

Our demo business unit had 1,862 data extensions. (See below)

Figure 2: Readiness summary, with the export option and DLO readiness highlighted

Signal	Result	How we read it
Inventory to target-model mapping	28 of 1,862	Data extensions that already have a DMO target assigned
Readiness scoring by asset	24 green · 3 amber · 1,835 red	Most assets flagged as redesign candidates in the first pass
Dependency-aware migration waves	17	Low-dependency candidates that could likely move in an early wave
DLO readiness	26 pass · 3 warning · 1,833 blocked	Very little is ready to land in Data Cloud as it stands

Marketing Cloud Engagement vs Marketing Cloud Next: why this is a re-platforming

Marketing Cloud Engagement to Marketing Cloud Next is a re-platforming, not a lift-and-shift. Marketing Cloud Next uses Data 360 data lake objects (DLOs) and data model objects (DMOs). Most data extensions, scripts, journeys, and automations must be redesigned rather than copied.

A data lake object (DLO) is a Data 360 structure that stores ingested source data. A data model object (DMO) organizes data into a standardized model that can be used across Data 360.

“1,833 blocked” looks alarming, but it confirms what experienced MCE architects already expect: a move to Marketing Cloud Next is a re-platforming, not a lift-and-shift. The value is in knowing where the work is, so it can be planned instead of discovered halfway through.

How the classification engine sorts your data extensions 

The DE Classification Engine placed all 1,862 data extensions into ten classes, each with a suggested next step. 

Figure 3: The DE Classification Engine, with the Archive and Unknown classes highlighted

Status	Class	DEs	Suggested direction in MC Next
Ready	Sendable	1,234	Contact Point Email or Phone; journey entries usually become segment- or audience-triggered
Ready	Suppression	9	Consent or preference records; rebuild around channel-level consent
Needs mapping	Archive	238	Candidate for deprecation; confirm with the business owner first
Needs mapping	Lookup	72	Related DMO or custom object; plan field mapping and relationships
Needs mapping	Transit	6	Pipeline connector; redesign the handoff in Data 360 or Flow
Needs mapping	Transactional	5	Flow-triggered or event-driven pattern; review orchestration
Needs mapping	Audience	4	Likely a Data 360 Segment entry source; review query logic
Needs redesign	Staging	131	No direct equivalent; redesign as a Data Stream, calculated layer or flow
Needs redesign	Mixed use	88	Serves several roles; split into clearer objects first
Needs redesign	Unknown	75	Not enough signals to classify; needs manual review

This is where 1,862 rows turn into ten conversations. 

Instead of asking “what about this DE?” hundreds of times, the team can ask “how do we handle staging tables?” once, and agree on a pattern.

Classification is not the same as clearance

The Sendable class holds 1,234 data extensions marked Ready, meaning that type of object has a clear landing pattern in MC Next. But open the list, and most individual DEs in that class still show Blocked.

Figure 4: The Sendable class, with the classification verdict highlighted

Figure 5: Individual Sendable DEs. Most show Blocked; one shows Ready with medium confidence and a suggested DMO target

That’s by design. The tool separates two questions: 

• What is this? (the class, and where that kind of object usually lands)
• Can this specific one move yet? (its own assessment, mapping and confidence)

The workspace says as much in its own verdict: mixed-use and low-confidence results “should still be treated as human-review candidates before migration sequencing.” 

That’s exactly how we’d use it: as the map that tells architects where to look, with the final call made by people who know the account, the data and the business.

How do you size a Marketing Cloud Next migration?

1. Put a realistic size on the project, early 

Discovery for a Marketing Cloud Next migration can take weeks. A first-pass classification gives the first workshop a structured view of the estate instead of a blank page. It won’t replace discovery, but it gives it a head start and a shared vocabulary.

2. Shrink the scope before you start 

The cheapest data extension to migrate is the one you don’t have to. Here, 238 DEs were flagged as archive candidates. Combine that with the unused and stale DEs from an [asset health check], and you have a strong case for a cleanup phase before migration: less to map, less to test, less to pay for in Data 360.

3. Plan an early pilot wave 

The scan suggested 17 low-dependency candidates for an early wave. 

That’s a sensible pilot shortlist: small enough to move quickly, independent enough not to break anything else.

4. Build the redesign backlog

131 staging, 88 mixed-use and 6 transit DEs were flagged for redesign. These are usually held together by Automation Studio SQL, which in Marketing Cloud Next typically moves to Data Streams, calculated insights, Data 360 transformations or Flow. Knowing the count up front means architects can design patterns, not one-off fixes.

5. Get consent and suppression right first 

Only 9 suppression DEs were found, but they matter most. The scan suggests rebuilding them around channel-level consent, the way Marketing Cloud Next handles it. 

Migrate and validate these before any sendable audiences.

6. Rethink journey entry, and give owners a clear review list

For sendable DEs, journey entries “usually become segment-triggered or audience-triggered starts”, so plan journey redesign alongside data mapping. And for the 75 DEs that couldn’t be classified, business owners get a named list with evidence.

Where a readiness scan fits in your Salesforce Marketing Cloud migration plan 

Our MCE to Marketing Cloud Next migration guide sets out a six-phase approach. A readiness scan does most of its work in the first two phases and feeds the rest:

Phase	How the readiness scan helps
1. Source audit	Inventory and classification of every data extension in the business unit
2. Data structuring	Suggested DMO targets, lookups and redesign candidates as a starting point for the data model
3. Connector setup	DLO readiness shows what can stream into Data 360 now and what needs work first
4. Journey migration	Sendable, audience and transactional classes highlight journeys that need new entry patterns
5. Sandbox testing and UAT	The classified list becomes a checklist to confirm each object landed correctly
6. Go-live and transition	Waves and archive candidates help decide what moves, what runs in parallel and what retires

How to get the most out of a readiness scan

• Run an asset health check first. Clean up broken queries and obvious clutter so the scan reflects the account you actually want to migrate.
• Treat the output as a working hypothesis. Walk each class through with an MCE architect and the business owner before it goes into a plan.
• Check what the scan can’t see. DEs used only in AMPscript, SSJS, CloudPages or external API calls need a separate review, and that code needs rebuilding in MC Next anyway.
• Re-run after each wave. Readiness changes as the team maps, archives and redesigns. Use the counts to show progress.

Start your Marketing Cloud Next migration with a readiness scan

The hardest part of any Marketing Cloud Next migration is the beginning: understanding what you have. On our demo account, the readiness workspace turned 1,862 data extensions into ten clear classes, a shortlist of 17 pilot candidates and 238 DEs that may not need to move at all. 

That’s not a migration plan. It’s something more useful at the start: a clear, structured picture that lets an experienced team build the right plan faster.

Planning your move to Marketing Cloud Next?

Book a Marketing Cloud Next readiness assessment. 

Our MCE architects will review your current account, validate what maps and what needs redesign, and help you shape a phased migration plan.