A large enterprise is implementing MDM for customer data. The business requires a real-time, transactional view of the customer that is always current, and it also requires the ability to trace the history of changes to the master record. The source systems must remain the systems of record. Which MDM implementation style and supporting feature should the data architect choose?

Co-existence style with a versioned canonical model to track historical changes

Consolidation style with no versioning

Registry style with a flat canonical model

Transactional style with a single current-state model

A financial services firm has separate systems for loans, deposits, and wealth management, each with its own customer data model. The firm wants to build an MDM hub that can accept data from all three systems without requiring each system to change its internal schema. Which canonical modeling technique should the data architect use?

Create a separate MDM hub schema for each source system to avoid transformation

Define a common customer model in the MDM hub and create mappings from each source system's schema to the common model

Use the loans system's customer schema as the standard and require the other systems to conform to it

Store all source data in a single table with generic columns for all possible attributes

A data architect is configuring a matching engine for a global customer database. The matching algorithm assigns weights to fields, but the architect notices that the current configuration produces too many false positives (unrelated records being merged). The architect wants to reduce false positives without significantly increasing false negatives. Which adjustment is most effective?

Decrease the match threshold so that more records are considered matches

Reduce the number of fields used in the matching algorithm

Remove weights from all fields so every field contributes equally

Increase the match threshold so that only higher-confidence pairs are auto-merged

A data architect is configuring a matching algorithm for supplier records. The algorithm uses weighted fields: legal name (weight 50), tax ID (weight 40), and address (weight 10). The system flags a match if the score is at least 60. Two supplier records have the same tax ID but different legal names and addresses. What is the match score, and what action should the system take?

Score of 50; not flagged as a match

Score of 40; not flagged as a match

Score of 60; flagged as a match

Score of 100; flagged as a match

A retail company wants to enrich its customer master data with household income and purchasing-power indicators to improve marketing segmentation. The company has only the customers' names and postal codes in its CRM. Which approach should the data architect recommend to achieve this enrichment?

Create a canonical model that includes income fields and populate them with null values for future manual entry

Use a data cleansing tool to standardize name and address formats, then infer income from name patterns

Derive income and purchasing power by analyzing the customer's purchase history within the CRM

Integrate a third-party demographic dataset and match records on postal code to append income and purchasing-power attributes

SalesforceCertified Data Architect

Domain 3Objective 1

Compare and Contrast the Various Techniques, Approaches and Considerations for Implementing Master Data Management Solutions (e.g., MDM Implementation Styles, Harmonizing and Consolidating Data from Multiple Sources, Establishing Data Survivorship Rules, Thresholds & Weights, Leveraging External Reference Data for Enrichment, Canonical Modeling Techniques, Hierarchy Management). DATA-ARCHITECT Practice Questions (Page 5)

Part of the MASTER DATA MANAGEMENT domain, which accounts for 10% of the DATA-ARCHITECT exam.

33questions here

7free pages

7concepts

10%of the exam

Curriculum map

DATA MODELING
CONCEPTUAL DESIGN
MASTER DATA MANAGEMENT
- Compare and contrast the various techniques, approaches and considerations for implementing Master Data Management Solutions (e.g., MDM implementation styles, harmonizing and consolidating data from multiple sources, establishing data survivorship rules, thresholds & weights, leveraging external reference data for enrichment, Canonical modeling techniques, hierarchy management).
  ‹1 456 7 ›
- Given a customer scenario, recommend and use techniques for establishing a "golden source of truth"/"system of record" for the customer domain.
- Given a customer scenario, recommend approaches and techniques for consolidating data attributes from multiple sources. Discuss criteria and methodology for picking the winning attributes (data survivorship rules).
METADATA MANAGEMENT
DATA ARCHIVING
4 more domains

7 Concepts in This Objective

MDM implementation styles
Data harmonization and consolidation
Data survivorship rules
Thresholds and weights in matching
External reference data enrichment
Canonical modeling techniques
Hierarchy management

Questions 21–25

21expert · hard
A large enterprise is implementing MDM for customer data. The business requires a real-time, transactional view of the customer that is always current, and it also requires the ability to trace the history of changes to the master record. The source systems must remain the systems of record. Which MDM implementation style and supporting feature should the data architect choose?
Select an answer first
22application · medium
A financial services firm has separate systems for loans, deposits, and wealth management, each with its own customer data model. The firm wants to build an MDM hub that can accept data from all three systems without requiring each system to change its internal schema. Which canonical modeling technique should the data architect use?
Select an answer first
23expert · hard
A data architect is configuring a matching engine for a global customer database. The matching algorithm assigns weights to fields, but the architect notices that the current configuration produces too many false positives (unrelated records being merged). The architect wants to reduce false positives without significantly increasing false negatives. Which adjustment is most effective?
Select an answer first
24application · medium
A data architect is configuring a matching algorithm for supplier records. The algorithm uses weighted fields: legal name (weight 50), tax ID (weight 40), and address (weight 10). The system flags a match if the score is at least 60. Two supplier records have the same tax ID but different legal names and addresses. What is the match score, and what action should the system take?
Select an answer first
25application · medium
A retail company wants to enrich its customer master data with household income and purchasing-power indicators to improve marketing segmentation. The company has only the customers' names and postal codes in its CRM. Which approach should the data architect recommend to achieve this enrichment?
Select an answer first

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Questions 21–25

A retail company wants to enrich its customer master data with household income and purchasing-power indicators to improve marketing segmentation. The company has only the customers' names and postal codes in its CRM. Which approach should the data architect recommend to achieve this enrichment?

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