Practise vocabulary for enterprise data architecture: MDM, golden records, data domains, enterprise data models, and data governance integration.
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MDM (Master Data Management) creates a single, authoritative ___ of key business entities — customers, products, suppliers — eliminating data silos.
A golden record is the definitive, trusted version of a master data entity. MDM consolidates data from multiple source systems, deduplicates, and creates one golden record that all systems reference — eliminating conflicting versions of 'customer X'.
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A ___ data domain groups related master data entities managed together — for example, the 'Customer' domain includes Customer, Contact, and Address.
A data domain groups related entities under unified governance. The Customer domain, Product domain, and Financial domain each have an owner, governance policies, and quality standards. This structures accountability for data quality.
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An Enterprise Data Model (EDM) provides a ___ view of all significant data entities and their relationships across the organisation.
An Enterprise Data Model (EDM) is a logical model showing key entities (Customer, Order, Product) and their relationships at a business level — technology-neutral. It's the 'lingua franca' for data discussions, enabling consistent data exchange between systems.
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___ integration ensures that each operational system subscribes to the MDM's golden record rather than maintaining its own customer data copy.
MDM-centric integration routes all master data through the MDM hub, which maintains the golden record and distributes authoritative data to consuming systems. Systems 'phone home' to MDM for customer data rather than maintaining separate copies.
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'___ at rest' means personal or sensitive data is stored in encrypted form in databases, file systems, and backups.
Encryption at rest protects stored data from unauthorised access — if a database file is stolen, the data is unreadable without the encryption key. This is a mandatory control under most security frameworks (ISO 27001, PCI-DSS, HIPAA).
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PR Description
Subject: Refactor User Profile API - Added Data Governance Metadata
During the recent update to the user profile API, we've incorporated metadata related to data governance policies. Specifically, we've added fields to track data lineage, ownership, and sensitivity levels for each user attribute. This aligns with our enterprise data architecture strategy of promoting a consistent understanding of data across all systems.
Which phrase best describes the purpose of this metadata addition within the context of the PR?
Insufficient – The question focuses on understanding how the metadata contributes to the broader enterprise data architecture. Option A describes schema validation, which isn't the primary goal here; option B is simply documentation, not governance. While option C accurately reflects the addition of controls for data quality and compliance, it's too broad. Option D misrepresents the purpose – adding metadata doesn't simplify the API by reducing fields.
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PR Description
Subject: Refactor User Profile API - Added Data Governance Metadata
During the recent update to the user profile API, we've incorporated metadata related to data governance policies. Specifically, we've added fields to track data lineage, ownership, and sensitivity levels for each user attribute. This aligns with our enterprise data architecture strategy of promoting a consistent understanding of data across all systems.
Which phrase best describes the purpose of this metadata addition within the context of the PR?
Insufficient – The question focuses on understanding how the metadata contributes to the broader enterprise data architecture. Option A describes schema validation, which isn't the primary goal here; option B is simply documentation, not governance. While option C accurately reflects the addition of controls for data quality and compliance, it's too broad. Option D misrepresents the purpose – adding metadata doesn't simplify the API by reducing fields.
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PR Description
Subject: Refactor User Profile API - Added Data Governance Metadata
During the recent update to the user profile API, we've incorporated metadata related to data governance policies. Specifically, we've added fields to track data lineage, ownership, and sensitivity levels for each user attribute. This aligns with our enterprise data architecture strategy of promoting a consistent understanding of data across all systems.
Which phrase best describes the purpose of this metadata addition within the context of the PR?
Insufficient – The question focuses on understanding how the metadata contributes to the broader enterprise data architecture. Option A describes schema validation, which isn't the primary goal here; option B is simply documentation, not governance. While option C accurately reflects the addition of controls for data quality and compliance, it's too broad. Option D misrepresents the purpose – adding metadata doesn't simplify the API by reducing fields.
9 / 14
PR Description
Subject: Refactor User Profile API - Added Data Governance Metadata
During the recent update to the user profile API, we've incorporated metadata related to data governance policies. Specifically, we've added fields to track data lineage, ownership, and sensitivity levels for each user attribute. This aligns with our enterprise data architecture strategy of promoting a consistent understanding of data across all systems.
Which phrase best describes the purpose of this metadata addition within the context of the PR?
Insufficient – The question focuses on understanding how the metadata contributes to the broader enterprise data architecture. Option A describes schema validation, which isn't the primary goal here; option B is simply documentation, not governance. While option C accurately reflects the addition of controls for data quality and compliance, it's too broad. Option D misrepresents the purpose – adding metadata doesn't simplify the API by reducing fields.
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// TODO: Add data lineage tracking to the 'Customer' domain.
During code review, Sarah comments on this commit:
'This change is good, but we need to consider how this new customer data is related to our existing product master data. Let's add some metadata indicating the source and transformations applied.'
Which term best describes Sarah's suggestion?
Sarah is referring to Metadata Management, which involves adding information about the origin and transformations of data – crucial for understanding its lineage and ensuring consistency within an Enterprise Data Architecture. A 'Data Silo' refers to isolated datasets; 'Master Data Record' is a specific instance of master data. 'Data Stewardship' is a role, not a technical concept.
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Mark sends the following message in the #data-architecture Slack channel:
'We need to ensure all new reporting dashboards pull data directly from the MDM for Customer data. We're seeing inconsistencies across different departments because they're using their own local copies.'
What does Mark primarily highlight regarding Enterprise Data Architecture?
Mark is discussing Master Data Management (MDM) – a core principle of ensuring a single source of truth for critical business entities like customers. 'Data Replication' is a *method* used to achieve this, but Mark's focus is on the overall MDM strategy. 'Data Virtualization' and 'Data Normalization' are distinct data management techniques.
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PR Description
Subject: Implement Data Quality Rules for Product Catalog
The team has implemented new data quality rules within the product catalog domain to ensure consistency in product attributes. These rules are defined as metadata and automatically enforced by the ETL process. This ensures that all systems maintain a consistent view of our products.
Which best describes the purpose of this PR's changes?
This PR focuses on Data Governance – specifically enforcing rules and policies to maintain data quality. The metadata defines the governance rules, ensuring consistency across systems. 'Data Modeling' is a broader architectural concept; 'Database Sharding' refers to database partitioning; and 'API Versioning' relates to API updates.
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During the daily stand-up, David reports:
'I'm working on integrating our new CRM system with the MDM for Customer data. We're using event-driven integration to ensure real-time updates.'
What does David's statement indicate about his work in relation to Enterprise Data Architecture?
David is describing Change Data Capture (CDC) – a key integration pattern where changes in the CRM system are immediately propagated to the MDM. This is crucial for maintaining data consistency and synchronizing master data. 'Batch Processing' involves periodic updates; 'Data Warehousing' focuses on historical reporting, and 'Big Data Analytics' uses large datasets.
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The IT security team is implementing measures to protect sensitive customer data. They are configuring the database to encrypt all Personally Identifiable Information (PII) at rest.
What does 'data at rest' refer to in this context?
'Data at rest' specifically refers to data that is stored in a persistent storage medium – such as databases, file systems, and backups – rather than being actively processed or transmitted. This ensures protection against unauthorized access if the storage media were compromised.
What does the "Enterprise Data Architecture Vocabulary" exercise cover?
Practise vocabulary for enterprise data architecture: MDM, golden records, data domains, enterprise data models, and data governance integration.
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How many questions are in "Enterprise Data Architecture Vocabulary"?
This exercise has 14 questions. Each one gives instant feedback with an explanation, so you can see exactly why an answer is right or wrong.
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