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Study guide for chapter 9 of the Data Architect course. Read the four modules first; this page helps you check what stuck.

About this study guide. It’s built only from this course’s own content and the published Salesforce exam guide’s list of objectives. It is never based on real exam questions, and it doesn’t claim to know what’s on the exam. If you’ve taken the exam, please don’t send me questions from it: the certification agreement forbids sharing them, and memorizing answers is the wrong way to become an architect anyway.

The exam guide says it doesn’t test integration-tool configuration, and this chapter is a data architect’s sampler, not the Integration Architect course. What the exam does care about is what integrations do to your data: keys, write authority, volume and completeness, and data moving between orgs. Platform numbers change, so check the current ones before you rely on them.

For the Exam

Tick them off as you go. Each one links to where it’s taught.

Before the arrow (supports LDV-1 and SDM-2)

• I zoom out to the landscape, then zoom in on one arrow and ask its data questions: initiator, direction, freshness, volume and shape, key, write authority, and who proves it arrived. (Zoom In on One Arrow)
• I separate who initiates from which way the data flows, and I know only the client sees the whole round trip. (Who Starts It Isn’t Which Way the Data Moves)
• I treat freshness as a requirement, not a default, and match the timing to the mechanism: a synchronous call when the caller waits, platform events for fire and forget, Change Data Capture to keep another system in step, the Bulk API for large scheduled loads. (How Current Does It Need to Be?)
• I know a database stores; a process calls: polling needs a process, often middleware, and polling for nothing is waste. Change Data Capture has a daily delivery allocation, counted per subscriber. (Asking Every Minute)
• I know Salesforce’s guidance for pulling changes on a schedule: getUpdated() and getDeleted() for intervals over 5 minutes; more often than that, let Salesforce send the change. (Asking Every Minute)
• I know the three traffic shapes, singles, sets and bulk; that more than 2,000 records is a good candidate for Bulk API 2.0, fewer for bulkified synchronous calls such as Composite; and to send only the fields that changed. (The Number of Zeros Applies to Integrations Too)
• I know integration volume becomes data volume: ownership, automation, sharing and storage. (Integration Volume Becomes Data Volume)

Keys and write authority (supports SDM-2, SDM-4 and MDM-2)

• I carry an external system’s key in an External ID field marked Unique, one-to-one, and upsert on it: no match creates, one match updates, more than one fails. (One Record, One Key)
• When one customer has several external records, I add records, not fields (a hierarchy, peers or a child object), never a key field per ERP. (When the Customer Is in Two ERPs, chapter 6: One Customer, Two ERPs)
• I know one key field with the source in the value is still one key per record, and a new partner is a new value, not a new field. (Steve Trucking: One Field, the Source in the Value)
• I know stable keys make retries safe (the start of idempotency). (Keys Make Retries Safe)
• I know a key isn’t authority, and enforce write authority in the org: record types, read-only fields for users, and an integration user with only the access its contract needs. (A Key Isn’t Authority)
• I know two-way movement still has one owner per field, and how unclear authority causes loops. (Two-Way Movement, One Owner per Field)
• I know a record ID from one Salesforce org isn’t an enterprise key in another: two orgs are two systems. (Keys Have Lifecycles Too)

Proof of delivery (supports MIG-1 and MIG-2)

• I know the client owns the conversation, and whoever knows what should arrive proves that it did; the server keeps its own promises and reports what it received. (Who Proves It Arrived?)
• I know “no errors” isn’t completeness: reconcile counts and, where it matters, control totals. (“No Errors” Isn’t Completeness)
• I design for restart and safe retries, and log every call: request ID, endpoint, response code and duration. (Know Where You Are, and Restart Gracefully, Log Every Call, Retries Are Normal; Make Them Safe)
• I know platform events and Change Data Capture events stay on the bus for 72 hours, subscribers resume by Replay ID, duplicates can happen, and proof needs my own return receipt. (The Return Receipt)
• I know the soft landing for partial failure, and I send the increment, not the universe. (Partial Failure, and the Soft Landing, Send the Increment, Not the Universe)
• I know the four shapes: request and reply, fire and forget, batch and events, and where each recovers. (Four Shapes of Integration)
• I know outbound messaging is supported but gets no further investment, and since Spring ‘26 sends no session ID. (Outbound Messaging: Know It, Don’t Start There)

The integration data contract (supports SDM-4)

• I can write an integration data contract for an arrow, eleven lines: initiator, direction, freshness, volume and shape, key, write authority, pattern, mechanism, proof of delivery, sensitivity and travel, and change. (An Arrow Needs More Than a Label)
• I go requirement, then pattern, then mechanism. (Requirements, Then Pattern, Then Mechanism)
• I know when to give another team a custom Apex REST endpoint instead of the standard APIs (one stable interface, my own logging and orchestration) and what it costs (code to maintain; API and Apex limits still apply). (A Contract Between Teams)
• I count every place the data rests on its way, logs and retry queues included, when it has to stay in a country. (Make Each Line Specific)
• For multiple orgs, I start with a contract per movement, and sometimes the contract says don’t move it (chapter 14). (Multiple Orgs, and “Don’t Move It”)

Where the rest lives. This chapter is about moving data. Not moving it (Salesforce Connect, mashups, data brought in on demand, zero copy: exam objective LDV-3) is chapter 14, Virtualization, Federation, and Zero-Copy (coming soon). Loading and extracting at volume is chapter 10, Migration and Synchronization.

Beyond the Exam

The exam is the floor, not the ceiling. These are the habits from this chapter that an architect needs, whether or not a question ever asks about them.

• Zoom out, then zoom in. Start with the landscape; then take one arrow at a time.
• Understand the traffic that’s coming, even when someone else designs the integration.
• Choose the mechanism after you understand the movement.
• A database stores; a process calls. Someone has to own the process.
• Data movement isn’t free. Every copy is another place to govern.
• Add records, not fields.
• Know the record. Know the owner. Then let the integration write.
• Whoever knows what should arrive proves that it did.
• If it can fail silently, it isn’t finished. A stopped integration is a data quality problem.
• Permission says can; architecture says should.
• Decide the interface between teams in the first weeks: the standard API or a wrapper you own.
• The contract outlives the technology.
• Treat every agent action as an integration, with keys, authority, idempotency and observability.

Words to Know

Term	In one line
Initiator	The system that starts the conversation (the client)
Data direction	Which way the business data moves, whoever starts it
Freshness	How current the data must be
Polling	Asking on a schedule whether anything changed
Singles, sets, bulk	One record at a time, small groups, or large volumes in one job
External ID	Another system’s key stored on the Salesforce record, used for matching
Upsert	Update the matching record if it exists, create it if not
Idempotency	Repeating an operation without unintended extra effects
Watermark / checkpoint	The record of how far an integration has safely got
Reconciliation	Comparing what was intended with what arrived
Proof of delivery	Evidence, held by the side that knows what should arrive, that it did
Return receipt	An acknowledgment sent back to say a message was received and processed
Request and reply	The client sends and waits for the answer
Fire and forget	The client sends without waiting for the outcome
Platform event	A message published on Salesforce’s event bus for subscribers
Change Data Capture	Events Salesforce publishes when records change
Replay ID	The position a subscriber uses to resume reading events
Custom Apex REST	Your own REST endpoint in Salesforce, written in Apex, in front of your objects
Integration data contract	A short record of what an integration may do to the data

Check Yourself

Short scenarios in the style of the course. Decide your answer before you open it.

1. Salesforce calls the ERP to get a customer's credit status. Which way does the data flow, and who initiates?

Salesforce initiates; the data flows ERP → Salesforce. Initiator and direction are separate questions, and the initiator (the client) is the one that sees the whole round trip. Reread Who Starts It Isn’t Which Way the Data Moves.

2. The team proposes creating a Salesforce record for every GPS reading: 200,000 a day. What do you ask first?

Why put 73 million readings a year into the transactional model? That’s a data architecture decision before it’s an integration one; the org may need only the latest position. Reread Integration Volume Becomes Data Volume.

3. A warehouse team says, "Snowflake will just poll Salesforce every minute." What's missing?

A database stores; a process calls. Something has to run the polling (usually an integration layer), with its own credentials, schedule and failures, and 1,440 calls a day mostly find nothing. Ask how current the data must be, then consider letting Salesforce send the changes (Change Data Capture), and count the events. Reread Asking Every Minute.

4. An external system needs Salesforce's changes about every hour, including deletions. What does Salesforce's own guidance suggest?

For intervals over 5 minutes, the SOAP API’s getUpdated() and getDeleted() return what changed and what was deleted in a window, instead of a full extract. More often than that, let Salesforce send the change. Reread Asking Every Minute.

5. The ERP retries a "create customer" call after a timeout and Salesforce ends up with two accounts. How should it have been designed?

Upsert on the ERP’s customer number in an External ID field marked unique, so a retry matches the existing record instead of inserting a duplicate. Reread Keys Make Retries Safe.

6. The customer exists in two ERPs, and someone proposes `NA_ERP_ID__c` and `EMEA_ERP_ID__c` on the Account. Your view?

That’s a key field per ERP: an anti-pattern. It hides repeating structure in fields and turns every new ERP into a schema change. Add records, not fields: child accounts, peer accounts, or a child object per ERP record, each with one key. Reread When the Customer Is in Two ERPs.

7. The integration log shows zero errors, but finance totals don't match. What happened, and who should have caught it?

Zero errors isn’t completeness: maybe fewer records were sent than intended, or values changed in transit. The side that knows what should have arrived proves it did: it reconciles counts and control totals against what it meant to send. Reread Who Proves It Arrived?.

8. A subscriber to platform events was down for a day. Can it catch up?

Yes, within the 72-hour retention: it resumes from its last Replay ID. It must also handle duplicates, because the same event can arrive twice. Reread The Return Receipt.

9. The requirement says "we need a REST integration for credit holds." What's wrong with that?

REST is a mechanism, not a requirement. The requirement is something like “agents see a credit hold within five minutes of the ERP change.” Start there, choose the pattern, then the mechanism, and write the contract. Reread Requirements, Then Pattern, Then Mechanism.

10. A partner's middleware team will send orders that touch four objects, and your data model changes every release. Standard API or custom Apex REST?

It depends on the team. If they know Salesforce deeply and can change quickly, the standard APIs work. If not, a custom Apex REST endpoint gives them one stable interface, lets Salesforce orchestrate the four writes and log every call, and absorbs your changes inside. The cost is code you maintain, inside Salesforce’s API and Apex limits. Decide in the first weeks. Reread A Contract Between Teams.

Explore

• Salesforce Certified Platform Data Architect Exam Guide (opens in a new tab), Salesforce Help (checked 2026-11-01): the official list of objectives and their weights. Always check the current version before you book the exam.
• Salesforce, Best Practices for Deployments with Large Data Volumes (opens in a new tab), Winter ‘27 (last updated September 18, 2026), checked 2026-11-01: the guide behind the exam’s Large Data Volumes section. Its integration rules are in module 1; its mashups are in chapter 14.
• Each module’s own Explore section lists the Salesforce documentation behind its facts, with the date checked.