資料架構與現實相遇的地方
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Data Architect 第 10 章，第 2 部分：大規模架構。上一章：整合與資料流動。
遷移是資料架構與現實相遇的地方。我們做過的每一個建模、品質、主資料和資料量決定，都會在幾百萬條記錄同時到達的那一天接受檢驗。而一次「載入成功」的遷移依然可能是失敗的：錯誤的所有人、斷開的關係、重複的客戶、一百萬封歡迎郵件、被鎖定的記錄，或者一個時間用完了的切換週末。
Image generated with AI. ⟲
Every CTA scenario has a legacy system to bring across, and the candidate has to say how the data comes in, how it’s cleaned and how it’s de-duplicated. This chapter is that answer, from the source extract to the moment the old system stops mattering, and then the copies that keep going. ⟲
One example runs through all five modules: Steve Trucking retiring RouteDesk, its old dispatch tool, with eight years and about 5 million deliveries. What comes into Salesforce, how it’s prepared, how it loads, what the automation does about it, and the weekend it all happens. Then the other direction: Salesforce, now the system of record, keeping Snowflake’s copy in step. ⟲
本章的思想
Section titled “本章的思想 ”- Migration is a quality project first, and a migration is an integration with an end. ⟲
- Migrate, archive or discard, and know why every class of data moves, or doesn’t. ⟲
- Prepare outside, then load the result: a preparation data store, the raw source kept, no step that loses fidelity, and three sets of keys (the source’s, the transformations, Salesforce’s). ⟲
- The model sets the load order, and every child finds its parent by a key, never by a name. ⟲
- The Bulk API is the loading dock behind the bank, and the dock still needs a plan: insert before upsert, sort by parent, the load user, and the IDs brought back. ⟲
- Any time you turn automation off, you own that business logic not happening. The bypass is part of the original design, tested on and off and deployed long before it’s needed. ⟲
- Production cutover should be boring: rehearsed, run from a runbook, loaded early and hidden by sharing, with go/no-go and a rollback clock decided in advance. ⟲
- **用四種方式證明它：**數量、合計、抽查和彙總報表。
- Getting data out isn’t leaving Salesforce. Migration has a defined start and end; synchronization is ongoing, and the mirror is never the master. ⟲
本章的路線
Section titled “本章的路線 ”五個模組，每個都可以單獨閱讀。
- Migration Is a Quality Project First. RouteDesk on the landscape; migrate, archive or discard; the preparation data store; Steve’s five steps; loading by keys; merged records and their children; three sets of keys. ⟲
- Loading at Volume. The teller window and the loading dock; Bulk API 2.0 and 1.0; insert, update or upsert; sorting by parent; the load user; bringing the keys back; rehearsing the whole run. ⟲
- Automation During the Load. The arrows a load sets off; don’t need it, simulate it, defer it; what a bypass looks like in Apex, flows and validation rules; sharing; the automation inventory. ⟲
- Cutover Weekend. The runbook; Day −7, Day −1, Day 0 and the rollback point; locking users out; the four proofs; authority moves on Day 0. ⟲
- Getting Data Out: Keeping Another System in Step. Salesforce stays the system of record; Snowflake needs a mirror. The ways out, PK chunking, keeping it current, a copy once or a copy forever. ⟲
架構師在這裡決定什麼
Section titled “架構師在這裡決定什麼 ”- **到底什麼要遷移：**遷移、歸檔還是丟棄，以及為什麼。
- **資料在到達之前如何變得合格，**以及每條記錄如何保持可追溯到它的來源。
- **載入計劃：**順序、鍵、併發、身分和所有權。
- **載入被允許觸發什麼，**以及正常執行如何恢復。
- **切換如何執行和證明，**以及回滾什麼時候不再是一個選項。
- Where migration ends, what keeps another system’s copy in step afterward, and who owns each value. ⟲
**考試之外：**AI 加快了遷移中分析的那一半：資料剖析、對映、異常檢測、編寫指令碼。一步一步地使用它，並追蹤每一條生成的命令。驗證、對賬和 go/no-go 依然是確定性的，由人負責。每個模組的結尾都會講 AI 帶來了什麼改變。
- Salesforce, General Guidelines for Data Loads （在新標籤頁中開啟） and Bulk API and Bulk API 2.0 Limits and Allocations （在新標籤頁中開啟）, checked 2026-11-01. ⟲
- Salesforce, Best Practices for Deployments with Large Data Volumes （在新標籤頁中開啟）, Winter ‘27, checked 2026-11-01. ⟲
- Integration Architect 課程：Bulk (coming soon)。