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Data Architecture & Large Data Volumes

Data architecture for the Platform Data Architect exam: modelling, MDM, large data volumes, migration and governance.

  • Advanced
  • 34 lessons
  • 8 modules
  • English

Designed and created by Salesforce Expert

$79
or $249 / year for all access Buy this course

What you'll learn

  • Model data for a platform with the limits this one has
  • Decide where the master record lives across several systems
  • Design for large data volumes before they arrive
  • Plan and execute a migration that can be verified
  • Set data governance somebody will actually follow

Course content

8 sections · 34 lectures

What this exam calls data architecture 3 lectures
  1. 1.1 The erasure request that could not be honoured
  2. 1.2 Brindlemere at scale — the numbers, the two orgs, and the four decisions this course keeps coming back to
  3. 1.3 What the exam actually is, what its guide is pinned to, and the three courses this one is not
Data modelling and database design 7 lectures
  1. 2.1 Grain first: what a record *is* before you decide what it holds
  2. 2.2 Master-detail, lookup, hierarchy, junction — the relationship decides the sharing, the roll-up and the lock
  3. 2.3 Object features are a bill you sign at design time — history, feeds, activities, roll-ups, indexes
  4. 2.4 A data model that obeys the sharing model you already have
  5. 2.5 Big objects against standard and custom objects — what you gain, and the four things you give up
  6. 2.6 Data skew — record locking, sharing recalculation, and the parent with too many children
  7. 2.7 Metadata about the model — business dictionary, lineage, taxonomy and data classification
Salesforce data management 7 lectures
  1. 3.1 Licence types are a data-architecture decision, not a procurement one
  2. 3.2 External users — the licence, the record access it can carry, and the model that has to follow
  3. 3.3 Persisting data consistently — where the platform will enforce it for you, and where it will not
  4. 3.4 Standard objects, custom objects, and what it costs to ignore the standard model
  5. 3.5 A single view of the customer across five systems of interaction
  6. 3.6 Two Salesforce orgs — consolidate, federate, or leave them apart, and how to tell which
  7. 3.7 Copy, reference or federate — a decision table you can defend in one sentence
Master data management 2 lectures
  1. 4.1 The four MDM styles, and which one a Salesforce org can actually be
  2. 4.2 Survivorship — picking the winning attribute, and keeping the reference data that explains why
Large data volume considerations 6 lectures
  1. 5.1 "Large" is not a row count — what actually gets slow, and in what order
  2. 5.2 Selectivity and indexes — designing the query before you design the table
  3. 5.3 Skinny tables, divisions, and the levers you do not control
  4. 5.4 Designing for volume — the model changes that keep an org fast when it triples
  5. 5.5 Archive, purge or keep — a retention plan the business will actually approve
  6. 5.6 Virtualised data — when the right answer is not to bring the data in at all
Data migration 4 lectures
  1. 6.1 A migration is a design, not a load — scope, grain, and deciding what does not come across
  2. 6.2 Quality at load time — the checks that have to happen before the first record lands
  3. 6.3 Loading large volumes fast — the levers, in the order you pull them
  4. 6.4 Getting data out — export, extract, and the copy you need before you migrate
Data governance 3 lectures
  1. 7.1 Designing a data model that can honour an erasure request
  2. 7.2 Classify before you protect — identifying personal and sensitive data, and what the platform can carry for you
  3. 7.3 A governance programme that survives its sponsor
The exam, and the org you now own 2 lectures
  1. 8.1 The exam run — 60 questions, 105 minutes, 58%, and how to read a scenario that has two defensible answers
  2. 8.2 The design review you can run on your own org this quarter, and where the track goes next

Requirements

  • CORE-210 Platform Administrator II, or equivalent senior experience
  • Working knowledge of the sharing model

Description

What the Platform Data Architect exam calls data architecture, taught as decisions with consequences: data modelling and database design, Salesforce data management, master data management, large data volume considerations, migration and governance.

Large data volumes are where most designs fail, and they are treated here as a first-class subject rather than an appendix — skew, selectivity, indexing and the archive strategy nobody wrote down.

Who this course is for

  • Senior administrators, consultants and architects preparing for Platform Data Architect.

Skills you'll practise

Data architectureLarge data volumesMaster data managementData migrationData governanceData modelling

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