Master and Reference Data Management Flashcards
What word has the following definition: Managing shared data to meet organizational goals, reduce risks associated with data redundancy, ensure higher quality, and reduce the costs of data integration.
master and reference data
_______________ refer to a structured system of representing data elements with unique values and corresponding human-readable representative text. In Master and Reference Data Management, these play a critical role in ensuring clarity, consistency, and accuracy in data usage. They help in standardizing the representation of key data elements, making it easier for users to understand and work with data.
Codes and descriptions
____________represent data elements in a structured, ordered manner, often organized as parent-child relationships. They provide a way to depict the relationships and dependencies between data elements. In Master and Reference Data Management, they are used to represent complex structures, such as organizational structures, product categories, or geographical locations.
Hierarchies
__________ involve the association of one data element to another or the translation of data from one format to another. In Master and Reference Data Management, these are used to establish relationships between data elements or to transform data from different sources into a common format. This metadata is crucial for achieving data consistency and interoperability, particularly when integrating data from diverse systems.
Mappings / Data Mappings
___________ involve grouping or categorizing data elements into predefined categories or classes based on shared characteristics or attributes. These provide a structured way to organize data and enable consistent categorization of entities. In Master and Reference Data Management, these are used to ensure that data elements are categorized in a standardized manner.
Classifications
______________provides control over master values and identifiers that enable consistent use across systems. It provides a single version of customers, accounts, materials, products.
Master Data Management (MDM)
The ___________ is a concept in Master Data Management (MDM) that represents a single, authoritative, and complete version of a specific data entity, such as a customer, product, or other critical business entity. It is the most accurate and reliable representation of the data, and it serves as the reference point for consistent data usage across an organization. It is typically created by merging and resolving data from multiple source systems to eliminate duplicates and discrepancies, resulting in a trusted and unified version of the data.
“Golden Record”
The _________ is a central repository or system within an organization where the authoritative and definitive version of master data is maintained. It is the source of record for key business entities and ensures data consistency and integrity across various systems and applications. It is responsible for maintaining and managing master values, such as customer details, product information, and other core data elements, to ensure that accurate and up-to-date data is available for decision-making and operational processes.
“System of Truth”
_____________ refer to the standardized and consistent data elements that represent essential business entities, such as customers, products, locations, or other key data categories. These values are part of Master Data Management (MDM) efforts and include unique identifiers, attributes, and relationships associated with each entity. These are carefully managed to ensure data quality, accuracy, and consistency, and they serve as the foundation for data-driven decision-making and operational processes across an organization.
“Master Values”
___________provides a standardized representation of data elements (in this case, product information), while ________ is a specific instance resulting from data reconciliation and merging to create the highest-quality and most trusted version of data.
Master Value
the Golden Record
Regarding reference data:
A(n) __________ refers to a structured collection of distinct and predefined data elements that serve as reference points for various data-related activities. These data elements are typically used to standardize and validate data entry, providing a finite set of permissible values for a specific attribute or field. This help ensure data consistency and accuracy by restricting the choices available to data users.
“List of Values”
Regarding reference data:
____________ is a hierarchical classification system used to organize and categorize data elements, concepts, or entities based on their inherent relationships and characteristics. It provides a structured framework for grouping and organizing data in a meaningful and logical manner. These are commonly used to create a hierarchical structure for reference data, enabling efficient navigation, search, and analysis of data.
“Taxonomy”
Regarding reference data:
___________ is a mechanism used to establish relationships or mappings between data elements from different sources, domains, or systems. It provides a way to link and identify corresponding data elements, ensuring that data can be consistently interpreted and related across disparate systems or reference data sources. These are valuable for data integration, data sharing, and data reconciliation.
“Cross Reference”
Question: Is Reference Data typically smaller or larger than Master Data, according to the DMBoK?
a) Smaller
b) Larger
c) The size varies depending on the organization
d) They are the same size
A
Why is Master Data important in reducing the risk associated with ambiguous identifiers?
Because Master Data provides a trusted version of truth
What role does Reference Data play in providing context for transaction data?
Reference Data provides context for both transaction data and Master Data
In what context should both Master and Reference Data be shared, as recommended by the DMBoK?
a) At the department level
b) At the project level
c) At the enterprise level
d) They should not be shared; each data type should be kept separate
C
Is Reference Data typically generated from within an organization or from external sources, as per the DMBoK?
It is primarily generated from external sources
How does Master Data contribute to reducing data-related risks in an organization?
By providing a trusted version of truth
Which type of data is considered a subset of the other—Reference Data or Master Data?
Reference Data is a subset of Master Data
What are some general facts about Master & Reference Data?
—Reference Data can be a subset of Master Data
—Both Reference and Master Data can provide context for transaction data
—Reference Data is typically smaller than Master Data
—Master Data reduces risk that might be associated with ambiguous identifiers
—Master Data requires a trusted version of truth for each instance of conceptual entities
—Both Master and Reference Data should be shared at the enterprise level
—Reference Data typically comes from outside the organization
In Master Data Management (MDM), a _______refers to an entity or individual that is of interest to an organization. These entities can include customers, suppliers, employees, partners, and any other entities with whom the organization interacts. Managing this data involves maintaining accurate and up-to-date information about these entities, which is crucial for various business processes such as customer relationship management, supplier management, and human resources.
Party
________is a key Master Data concept that encompasses items or goods offered or managed by an organization. This data management involves maintaining details about their descriptions, specifications, pricing, and other relevant attributes. Effective Master Data Management of this, is essential for inventory control, sales, marketing, and supply chain operations.
Product
The ________ concept pertains to the hierarchical organization of legal entities, financial entities, and their relationships within an organization. This data includes legal entities, subsidiaries, holding companies, tax structures, and financial reporting structures.
Legal / Financial Structure
_________ data in Master Data Management involves the precise information related to entities such as offices, facilities, warehouses, and geographic regions. Effective data management of this concept is vital for logistics, real estate management, and ensuring accurate addressing for customers and suppliers.
Location
______________involves the design and maintenance of these that define the structure, relationships, and attributes of master data entities. It ensures that data elements are organized and structured in a standardized way, facilitating consistent data representation and storage.
“Data Model Management”
__________ is the process of collecting and ingesting data from various source systems into the MDM system. This step involves capturing data from different sources, such as databases, applications, and external providers, and preparing it for MDM processing.
Data Acquisition
__________, __________, and _______refers to the activities aimed at ensuring the quality and consistency of master data. This increase the data’s value and usability.
“Data Validation, Standardization, and Enrichment”
_____________involves identifying and handling duplicate or conflicting instances of master data entities. This step ensures that each entity is represented by a single, accurate Golden Record.
“Entity Resolution”
__________ pertains to the distribution of master data to various systems and applications across the organization. It ensures that consistent, up-to-date master data is available where needed. ________________ involves assigning responsibilities and ownership for the management of master data, including data governance and data quality tasks.
“Data Sharing”
Stewardship
The ___________ is a centralized and specialized component of a Master Data Management (MDM) system. It is designed to manage, maintain, and control master data for key entities like customers, products, locations, and more. It is responsible for ensuring the accuracy, consistency, and quality of master data.
Master Data Hub
Related to a Master data hub, these represent the different source systems and applications that rely on master data for their operations
Spokes
The Master Data Hub is in charge of _____ and ______ the management of master data across the organization. It oversees the processes related to what 5 things?
coordinating and controlling
data acquisition, validation, standardization, enrichment, and distribution.
The Master Data Hub interacts with __________ to extract, consolidate, and synchronize master data from various sources.
source systems
_________ refer to the places where master data is persisted and managed. These can include databases, data warehouses, and other storage solutions. The Master Data Hub ensures that data within these remains consistent and up to date.
Data stores
Related to data sharing, a __________is an approach that involves creating a centralized application interface or hub for accessing and updating Master Data. In this approach, the master data exists primarily within this system, which serves as the system of record for the data. Users and applications interact with the it to retrieve, modify, and manage master data. It ensures that all transactions and updates related to master data are captured and synchronized.
Transaction Hub
In the context of data sharing, a _______ is an approach where an index or directory is used to point to the location of Master Data within various systems of record. Instead of physically storing the master data, this contains metadata and pointers that direct users or systems to the authoritative source of the data. It helps maintain a clear reference to where the master data resides and enables users to access the most current and accurate data directly from the source system.
Registry
In this approach for managing master data, individual systems of record manage their local copies of master data specific to their applications. However, these local copies are periodically made available from a central data sharing hub. This data sharing hub acts as the system of reference for master data, ensuring that data is synchronized, consistent, and available for use across the organization.
Consolidated
True or False: Both Master Data and Reference Data are forms of Data Integration
True
__________ is the process of combining, harmonizing, and unifying data from various sources to provide a coherent view of information.
Data Integration
These metrics assess the accuracy, completeness, consistency, and compliance of master and reference data. They measure the extent to which data conforms to established quality standards, regulatory requirements, and business rules.
Data Change Activity:
Data Quality and Compliance
These metrics track the frequency and volume of changes made to master and reference data over time. They provide insights into data volatility, the rate of updates, and the impact of changes on data integrity.They measure the volume of data shared and how frequently it is accessed and utilized, providing insights into data relevance and value.
Data Change Activity
These metrics measure the processes of acquiring and using master and reference data. They evaluate how data is collected, integrated, and utilized by various systems, applications, and users within the organization.
Data Ingestion and Consumption
These metrics define and measure the performance and quality standards that must be met regarding master and reference data. They specify expectations for data availability, accuracy, and timeliness and assess whether these SLAs are being achieved.
Service Level Agreements (SLAs)
These metrics assess the extent to which data stewardship responsibilities are defined and assigned within the organization. They measure the coverage of data stewardship roles, ensuring that individuals or teams are responsible for managing and governing data.
Data Steward Coverage
These metrics calculate the overall cost associated with managing, maintaining, and using master and reference data. It includes costs related to data storage, data quality efforts, governance, infrastructure, and personnel.
Total Cost of Ownership (TCO)
These metrics evaluate the extent to which master and reference data are shared across systems, applications, and users.
Data Sharing Volume and Usage:
