CCNA Data Management Questions

Upsert matches records against the legacy custom External ID field, updating existing Accounts and inserting new ones in a single Data Loader operation. This satisfies the requirement to update and insert simultaneously without splitting the load or risking duplicate creation.

Reducing the Data Loader batch size lowers the number of records committed per transaction, shortening each lock's duration and shrinking the contention window that triggers system lock errors. This directly satisfies the stem's requirement to mitigate record locking during bulk inserts, since smaller batches release row locks sooner, letting competing operations proceed.

Email matching supports both exact and fuzzy comparison modes, letting Salesforce flag near-duplicate Leads whose addresses differ only by typos or casing. This directly satisfies the stem's requirement that duplicate Leads be identified through configurable standard Matching Rule criteria, since Email is one of the standard matchable Lead fields.

External ID fields enable upsert operations and reliable relationship mapping during migration, preventing duplicate records and broken lookups. This satisfies the stem's data structuring requirement, since external IDs let the migration match legacy keys to Salesforce records deterministically.

Data Export Service provides scheduled, automated exports of Account and Opportunity data in CSV format directly from Setup, with a weekly interval and manual or scheduled delivery. This satisfies the requirement without external tooling or API development.

REGEX validation rules evaluate the entered phone or postal code against a defined pattern at save time, blocking malformed values before they persist. This enforces the data-quality constraint during user entry, which is exactly what Universal Containers requires.

A validation rule enforces the industry field on save, blocking record creation until populated. Unlike page layout requirements, which only apply in the UI, validation rules fire for all entry paths including imports and APIs, guaranteeing the constraint holds universally.

TRIM() strips leading and trailing spaces from the email value before comparison, so a validation rule can reject entries containing stray whitespace. It targets exactly the constraint in the stem, unlike functions that only alter case or substitute characters.

Data Import Wizard handles up to 50,000 records and supports simple updates to standard objects like Contact via CSV, with built-in duplicate matching. It suits 500 records without requiring the Data Loader's external client or API setup.

Matching Rules define the fields compared to identify duplicates, while Duplicate Rules determine the action taken when a match is found, including blocking save. Configuring both alerts users and prevents duplicate Contact creation in real time, satisfying the manager's requirement.

Master-detail creates a dependent relationship where the child Shipment__c record inherits the parent Account's sharing and ownership, and cascade deletion removes shipments automatically when the Account is deleted. This directly satisfies the stem's requirement that deleting the Account also deletes related Shipment records.

Data Loader handles custom objects alongside most standard objects, whereas Data Import Wizard covers a limited set of standard objects plus custom objects only through its restricted interface. This breadth satisfies the migration's requirement to load custom object records at scale.

A junction object carries two master-detail relationships, one to Account and one to Product, producing the many-to-many association. Master-detail also makes the junction's sharing and deletion behaviour dependent on both parents, which a lookup-based structure would not provide.

The Mass Delete Records tool clears selected standard object records in bulk from a Developer Edition sandbox, letting the administrator remove sample data quickly rather than deleting records individually. It targets specific objects and criteria, matching the requirement to clear standard object records efficiently.

Inactive currencies cannot be selected on opportunity records, so historical opportunities in those currencies would fail to load or default incorrectly. Temporarily reactivating each currency in Company Information restores it as a selectable option for the data load, satisfying the multi-currency migration constraint.

Master-detail children inherit the parent and cannot be reparented unless the field's 'Allow reparenting' setting is enabled. The error therefore indicates that checkbox is unticked on the Project__c to Milestone__c relationship, blocking the migration's reassignment of Milestone__c records.

Data Loader validates CurrencyIsoCode against the org's active currency records, so the CSV must contain valid, active three-letter ISO codes matching enabled currencies. Inactive or malformed codes cause failures in multi-currency organisations, making this verification essential before migration.

Apex triggers query and aggregate child records, then write the totals onto the parent, bypassing the master-detail requirement entirely. This satisfies the lookup and sibling-object constraint, since standard roll-up summaries only work across master-detail relationships.

Smaller Data Loader batches reduce the number of records per transaction, so cascading triggers consume less CPU time before the governor limit is reached. Temporarily deactivating non-essential triggers removes their CPU cost entirely, letting the remaining deletions complete.

The Bulk API is designed for large data volumes and can process records in parallel, significantly reducing migration time. It is more efficient than the SOAP API for millions of records. However, the consultant should be aware of governor limits and potential record locking. Using Bulk API with parallel processing is a best practice for large migrations.

Fuzzy matching compares text using phonetic and edit-distance algorithms, so minor spelling variations and typos in company names still register as matches. This satisfies the requirement to catch duplicate accounts created through slight name misspellings, which exact matching would miss.

Account Teams and Opportunity Teams model shared ownership across a territory, letting multiple users collaborate on one account or deal with defined roles and access. This reflects territory-based selling where several reps contribute to the same customer.

State and Country Picklists convert free-text address fields into standardised ISO-coded values, and Data Loader maps legacy entries to those picklist codes during migration, satisfying the automatic standardisation requirement across thousands of messy Account records.

Loading Accounts first satisfies the lookup relationship dependency, since Contacts and Opportunities reference the Account parent. Child records cannot resolve their AccountId until the parent exists, so this ordering prevents orphaned or failed rows during migration and preserves referential integrity across the three objects.

Record-Triggered Flow runs after the Account update and can loop through related Contacts, updating each mailing address only when the 'Sync Address' checkbox is true. This satisfies the stem's conditional, child-record update requirement declaratively, without Apex, and executes in the same transaction as the parent save.

Loading parents first generates the Salesforce record IDs needed for lookup matching. Exporting those IDs and mapping children via an External ID field preserves the hierarchy across legacy systems, satisfying the constraint of linking child accounts to their correct parents without manual rework.

Validation rules, triggers, and workflows fire on every inserted record, multiplying processing time across millions of rows and causing API timeouts. Temporarily disabling them lets the load complete within governor limits, satisfying the requirement to optimise performance and prevent timeout errors during migration.