DATA MANAGEMENT

GLOSSARY
The Standard Glossary of
Data Management Concepts
Developed by professional data practitioners to establish standard
terminology and meaning for the practice of data management,
with definitions, related terms and commentary

Version 0.2.1
August 2017

www.EDMCouncil.org
INTRODUCTION

About the Data Management Glossary

On the request of the membership, the EDM Council has initiated the formal creation of the Data
Management Glossary. The goal is to formalize the business terminology used to describe the practice of
data management. To achieve this goal, we organized a group of industry practitioners and asked them
to impose rigor on the definition of terms and to provide clarity needed to ensure consistent collaboration
among organizational stakeholders.

All EDM Council members are invited to offer critiques and alternative suggestions to the Data
Management Glossary. For each term in the glossary, there is a hyperlink ( Send feedback on this term)
which will assist you in providing feedback.

We are starting with 120 business concepts in six core data management categories (data architecture,
roles & responsibilities, provisioning, metadata, governance and data quality). We want to make sure the
terms, definitions, synonyms and descriptions align with your data management programs. We
encourage you to contribute additional terms and internal glossaries in support of this initiative. You can
also direct your critiques and alternative suggestions to John Bottega, Head of Best Practice for the EDM
Council (908-501-3826, jbottega@edmcouncil.org).

About the EDM Council

The EDM Council is a non-profit trade association established by participants in the financial industry to
define content standards and document best practices for implementing data management. The 200+
global member firms and more than 7,000 professionals of the EDM Council represent banks, asset
managers, data vendors, technology companies, consultants, academia and regulators across the global
financial system.

Data Management Best Practice

The EDM Council defines the capabilities and processes that are required to implement sustainable data
management, based on what does and does not work in the real world. Our best practice agenda is
created and verified based on the collective experience of individuals that have earned their expertise by
addressing the realities of financial service operations. The results of our research and documentation are
available to our constituents as a benefit of membership.

A key component of the data management best practices is DCAM – the Data
Management Capability Assessment Model. DCAM is the industry standard
guideline on the practice of data management – used as a framework for
establishing data management programs, obtaining alignment from stakeholders
and benchmarking progress. DCAM defines the core criteria for data management
strategy, business case, operating model, content engineering, data quality and governance.

For more information:

www.EDMCouncil.org

EDM Council – Data Management Glossary | 2017 i

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ABOUT THIS EDITION
Published August 2017

Categories of Terms
This edition includes definitions for the first 2 categories of terms – Function/Role and
Sourcing/Provisioning, totaling 25 terms. Additional categories and terms will be added in subsequent
releases.

FUNCTION / ROLE ......................................................................................................................... 1

Function: Business Data Stewardship ...................................................................................................... 1
Function: Data Architect .......................................................................................................................... 2
Function: Data Control ............................................................................................................................ 2
Function: Data Governance ..................................................................................................................... 3
Function: Data Officer ............................................................................................................................. 3
Function: Data Quality ............................................................................................................................ 4
Function: Metadata Management .......................................................................................................... 4
Function: Technical Data Stewardship .................................................................................................... 5
Function: Technology Architecture .......................................................................................................... 5
Role: Chief Data Officer ........................................................................................................................... 6
Role: Data Consumer ............................................................................................................................... 6
Role: Data Owner .................................................................................................................................... 6
Role: Data Sponsor .................................................................................................................................. 7
Role: Stakeholder .................................................................................................................................... 7
Role: Subject Matter Expert (SME) .......................................................................................................... 7

SOURCING/PROVISIONING ......................................................................................................... 8
Authoritative Data Domain ..................................................................................................................... 8
Authoritative Data Source ....................................................................................................................... 8
Authoritative Provisioning Point (APP) .................................................................................................... 8
Data Domain ........................................................................................................................................... 9
Data Lineage ........................................................................................................................................... 9
Golden Record ......................................................................................................................................... 9
Provisioning Point .................................................................................................................................. 10
Source of Origin ..................................................................................................................................... 10
System of Origin .................................................................................................................................... 10
System of Record ................................................................................................................................... 10
DATA QUALITY ............................................................................................................................ 11
Accuracy ................................................................................................................................................ 11
Completeness ........................................................................................................................................ 11
Conformity............................................................................................................................................. 11
Consistency ............................................................................................................................................ 12

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 Coverage ............................................................................................................................................... 12
Data Harmonization .............................................................................................................................. 12
Data Normalization ............................................................................................................................... 12
Data Profiling ........................................................................................................................................ 13
Data Quality .......................................................................................................................................... 13
Data Quality Decay Rate ....................................................................................................................... 13
Data Quality Dimensions ....................................................................................................................... 13
Data Quality Rule .................................................................................................................................. 14
Data Transformation ............................................................................................................................. 14
Exception Handling ................................................................................................................................ 14
Timeliness .............................................................................................................................................. 14
Uniqueness ............................................................................................................................................ 14

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© 2017 EDM Council. All rights reserved.
DATA MANAGEMENT GLOSSARY
Terms are organized alphabetically by category

FUNCTION / ROLE

Function: Business Data Stewardship

Definition The function that implements and/or executes the data management program for its
respective business data domain(s).

Description The Business Data Stewardship function must understand the business and data
manufacturing processes to ensure that the data is fit for its intended purposes. The function
includes (but not limited to):
• Defining and establishing the domain boundaries in collaboration with peer Business Data
Stewards
• Ensuring that all data management processes comply with organizational policy and
standards
• Capturing and verify data requirements in collaboration with data consumers
• Source and provision data for use by business or other consuming applications
• Ensuring that data is consistently defined, aligned to business concepts and captured as
metadata
• Designing, executing and monitoring data controls and transformation processes
• Managing data quality including profiling, remediation, business rules and validation
processes
• Coordinating across functions to define and implement data sharing agreements, security
levels, privacy restrictions and data retention policies

Possible Role • Business Data Steward (Executive)

Titles • Front Line Data Officer
• Functional Data Officer
• Data Domain Steward
• Data Custodian
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 Function: Data Architect
Definition The function that defines and implements the data content strategy for a given subset of
data.

Description The Data Architecture function provides the “content engineering” bridge between business
applications and technology implementation. The focus is on content management including
how the data will be identified/defined as well as how to access it across the organizational
ecosystem. The function of Data Architecture includes understanding the scope of data
needed to satisfy business requirements as well as ensuring that the data is aligned to its
precise meaning. The function includes (but is not limited to):
• Designing the data architecture processes
• Establishing the operating model required to execute the defined data engineering
processes
• Establishing and implementing the framework for conceptual and logical data modeling
• Defining logical domains of data in collaboration with business and IT
• Implementing a unified view of data meaning across the enterprise

Possible Role • Data Architecture Executive

Titles • Head of Data Architecture
• Data Architect Manager
• Data Architect
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Function: Data Control

Definition The function that sets the enterprise data risk controls framework and strategy.

Description The Data Control function is the first line of defense against risk from ineffective data
management practices. This includes the identification of key risk indicators as well as
reporting of key risk and performance indicators to executive management. The function
includes (but not limited to):
• Designing and implementing an enterprise-wide data risk governance framework
• Establishing data policy and standards for mitigating risk from data
• Defining and implementing risk profiling, assessment and oversight processes
• Developing risk training and tools to ensure compliance with risk mitigation objectives
• Monitoring and enforcing compliance with data policies and standards

Possible Role • Data Control Executive

Titles • Head of Data Control
• Data Control Manager
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 Function: Data Governance
Definition The function that defines and implements the standards, controls and best practices of the
data management program in alignment with strategy.

Description Data Governance is responsible for creating and implementing a “data control” environment.
According to the Basel Committee on Banking Supervision – a data control environment
consists of a set of policies governing all aspects of data acquisition, distribution, integration
and usage that are sanctioned by executive management, based on standards, implemented
across the data lifecycle, with clear accountability and monitored by audit. The function
includes (but is not limited to):
• Designing and implementing the framework (including associated processes) necessary to
sustain a data control environment
• Establishing the operating model required to achieve governance objectives
• Defining and implementing policy, standards and operating procedures
• Establishing and implementing the data accountability mechanisms
• Developing and implementing metrics needed to monitor/report on data management
progress
• Designing and implementing data governance training programs

Possible Role • Data Governance Executive

Titles • Head of Data Governance
• Data Governance Manager
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Function: Data Officer

Definition The function performed by an executive responsible for the strategy and implementation of
the data management program at a geographic, line-of-business or functional level.

Description Depending on the structure of the organization, the Data Officer function may fulfill the same
responsibilities as the CDO. In addition, the function includes (but not limited to):
• Ensuring the data management program is on track to deliver against objectives, goals
and expectations
• Ensuring business data ownership/stewardship
• Securing the resources required for execution
• Ensuring that the data management program is implemented in accordance with
standards, policies and procedures
• Managing collaboration with technology, operations and other cross-organizational control
functions
Possible Role • Regional Data Officer
Titles • Group Data Officer
• [Business name] Data Officer
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 Function: Data Quality
Definition The function that ensures the data being used for operating processes is fit for its intended
purpose.

Description The function includes (but not limited to):

• Defining data quality requirements in collaboration with Stakeholders
• Designing the data quality processes (i.e. validation and remediation) to ensure that data
is fit-for-purpose
• Establishing and implementing the data quality operating model
• Facilitating the prioritization and escalation of cross-domain data remediation
• Defining the data quality measurement criteria and reporting framework
• Delivering training to achieve adoption of the data quality operating model and associated
processes

Possible Role • Data Quality Executive

Titles • Head of Data Quality
• Data Quality Manager
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Function: Metadata Management

Definition The function that ensures the documentation, definition, and implementation of metadata.

Description The Metadata Management function is responsible for the quality, implementation, recording
and use of metadata. The metadata management function supports the business and
technical data stewards to ensure compliance with policy and the adoption of metadata
standards. The function includes (but not limited to):
• Establishing the metadata management framework and associated processes
• Defining and implementing the operating model for metadata management
• Selecting and implementing the metadata management tool sets in accordance with
internal guidelines
• Documenting content in the metadata repository
• Monitoring the completeness and accuracy of metadata
• Developing and delivering training to achieve adoption of the operating model associated
processes

Possible Role • Metadata Management Executive

Titles • Head of Metadata Management
• Metadata Manager
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 Function: Technical Data Stewardship
Definition The function that manages the technical implementation of the data management program.

Description The Technical Data Stewardship function manages the technology (i.e. databases; data marts;
data warehouses) and executes the physical implementation of the data elements associated
with selected data domains. The function includes (but not limited to):
• Designing, building and managing the technical infrastructure associated with a selected
data domain
• Aligning business elements with their associated data components
• Translating business and data elements into technical specifications
• Defining and managing technical service level agreements
• Defining the technical aspects of data quality, transformation and movement controls
• Monitoring and remediating data defects against established quality thresholds
• Establishing and implementing root cause analysis of data defects
• Managing technical metadata

Possible Role • Technical Data Steward (Executive)

Titles • Data Custodian
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Function: Technology Architecture

Definition The function that supports the technical design, approach and toolset selection in alignment
with the data strategy.

Description The Technology Architecture function ensures the objectives of the data management
program can be made operational. The function includes (but not limited to):
• Translating business requirements into the technology architecture and systems design
(blueprint)
• Aligning the business technology blueprint to enterprise architectural policy and
guidelines
• Manage infrastructure capacity, systems design, transmission capability and analytical
platforms
• Evaluate and recommend vendor solutions

Possible Role • Technology Architecture Executive

Titles • Technology Architect Manager
• Technology Architect
• Solution Architect
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 Role: Chief Data Officer
Definition The most senior executive in the enterprise responsible for the strategy and implementation
of the data management program.

Description The function includes (but not limited to):

• Establishing and maintaining the data management program
• Understanding business requirements and aligning them to the objectives of the data
management program
• Defining the strategy and operational framework needed to implement the data
management program
• Documenting the business case and aligning it to the budget/funding mechanisms
needed for program implementation and sustainability
• Defining the data quality framework necessary to ensure trust and confidence in data
assets
• Defining the data architecture framework for ensuring a unified view of meaning across
the organization
• Establishing the standards, policies and procedures for the data management program
• Defining and implementing the data governance and organizational structures needed to
support the objectives of the data management program
• Ensuring stakeholder understanding, alignment and commitment to the objectives of the
data management program

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Role: Data Consumer

Definition A process, application or stakeholder that receives or uses data from a data producer.

Description The Data Consumer establishes requirements and quality expectations for the data.
Consumers need assurance that the data is fit for its intended use and that the appropriate
use of the data is aligned to data management, governance and risk management policy.
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Role: Data Owner

Definition The person with overall accountability for the meaning, content, quality and distribution of a
given set of data.

Description The Data Owner is accountable for the quality of a given data domain or set of data. This
includes the quality of the data as well as how the data is defined, manufactured, identified,
maintained, delivered and consumed. The Data Owner may not be directly involved in the
curation and maintenance of the data, but they are accountable for ensuring that it meets
quality criteria and is in alignment with organizational standards.
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 Role: Data Sponsor
Definition An executive responsible for ensuring adequate funding of the data management program.

Description The Data Sponsor owns the P&L for the data management program and the allocation of
resources needed to mitigate the risk of service interruption. In addition to budgets and staff,
this includes understanding data dependencies as well as the ensuring that the contractual
obligations associated with third party data procurement are fulfilled.

Possible Role • Data Domain Sponsor

Titles
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Role: Stakeholder
Definition An interested participant (producer, consumer, supporting process) in the data ecosystem.

Possible Role • Involved Party

Titles
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Role: Subject Matter Expert (SME)

Definition An individual who is an authority in a business process, data manufacturing process or
application.

Possible Role • SME

Titles
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SOURCING/PROVISIONING

Authoritative Data Domain

Definition A Data Domain that has been designated, verified, approved and enforced by the data
management governing body.

Synonyms Authorized Data Domain

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Authoritative Data Source

Definition An officially designated system or repository for data that has been determined to be reliable
and accurate.

Description An Authoritative Data Source has been designated by the data management governing body
as the official source of a specific Data Domain. Required use of the authorized source is
driven by established policy and standards.

Synonyms • Golden Source

• Authorized Data Source
• Single Authoritative Source
• Designated Repository
• Publication Point
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Authoritative Provisioning Point (APP)

Definition A Provisioning Point that has been designated by the relevant data management governing
body as providing data from an Authoritative Data Domain.

Description Authoritative Provisioning Points are designated by the organization’s governing body after the
content has been rationalized against internal data engineering standards for meaning,
structure and format. As part of that designation the provisioning point includes adequate
data controls to ensure data remains fit for purpose. Best practice is that an Authoritative
Provisioning Point would be registered in the Enterprise Provisioning Registry.

Synonyms • Provisioning Point (Authorized, Approved)

• Data Service Point (Authorized, Approved)
• Data Delivery Service (Authorized, Approved)
• Data Access Point (Authorized, Approved)
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 Data Domain
Definition A logical representation of a category of data that has been designated and named.

Description Data Domains are not physical repositories or databases. Instead, they are “logical”
categories or groupings of data that are deemed important and necessary to a firm’s normal
business operation. Data Domains include both internally generated data as well as externally
acquired data. Examples of Data Domains might include “product data;” “customer data;”
“trade data;” “pricing data;” “index data;” “risk data,” etc. It is imperative that these strategic
categories of data are identified, defined and inventoried to ensure their proper maintenance
and use throughout the organization.

Synonyms • Data Subject Area

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Data Lineage

Definition Documentation of the sequence of movement and/or transformation of data as it flows

between the consumer and the source(s).

Description Data Elements may have multiple sources and end consumers. Data Lineage describes the
chronology of ownership, custody and location of data. Data Lineage provides a visual
mapping of the movement and changes in data from system to system. The goal is to ensure
that the data consumed is equivalent to the data delivered. Data Lineage provides a mapping
of data for use in impact analysis and operational risk integrity. The complete lineage will
document the full data flow and capture metadata about the movement and transformation of
the data element. Lineage may include a mapping of the data controls. Data Lineage is
commonly confused with Data Traceability and Data Provenance and should be understood in
relationship to one another.
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Golden Record
Definition A single, precisely defined, verified and officially designated version of data.

Description The Golden Record is designated by a business or operational process to indicate that the
data has been validated as fit for its intended purpose. A Golden Record should be used for
all applications and enforceable by policy.

Synonyms • Master Record

• Golden Copy
• Single Version of the Truth
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 Provisioning Point
Definition A service from which data associated with a Data Domain can be acquired after it has been
sourced.

Description The purpose of a Provisioning Point is the distribution of data from a given data domain to
ensure the appropriate source of data throughout the organization. Provisioning Points can
be executed in either physical repositories or via virtual access and help establish a ‘control
environment’ for data throughout the organization.

Synonyms • Data Service Point

• Data Delivery Service
• Data Access Point
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Source of Origin
Definition The genesis of data content prior to being captured electronically.

Description The Source of Origin refers to the source of a Data Element. The data value may have been
created by an individual in the business process, manually captured in a document, sourced
manually or captured electronically from an external provider. For example, the prospectus
would be the Source of Origin for the instrument record in the Security Master Database.
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System of Origin
Definition Any application or repository where data is initially captured.

Description A System of Origin is the point at which information has been introduced (without validation
or remediation) into the organization. If the System of Origin is considered valid without
reconciliation, then the System of Origin could also be classified as the System of Record.
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System of Record
Definition The Authoritative Data Source for the specified Data Element after it has been remediated
and validated.

Description SORs are repositories of data that have been screened, validated and exceptions remediated.
To ensure data integrity there must be only one System of Record for a logical category of
data.
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DATA QUALITY

Accuracy
Definition A measurement of the veracity of data to its authoritative source.

Description Accuracy is a measurement of the precision of data. It can be measured against either
original documents or authoritative sources and validated against defined business rules.
Accuracy is one of the seven Data Quality Dimensions.

Examples:
• Records that are wrong at a specified time (i.e. a record with an incorrect maturity date)
• Records that haven’t been refreshed or updated
• Records at the wrong level of precision (i.e. prices that were originally quoted at three
decimal places, but cut-off and stored at two decimal places)

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Completeness
Definition A measurement of the availability of required data attributes.

Description Completeness measures the existence of required data attributes in the population of data
records. Completeness is one of the seven Data Quality Dimensions.

Examples:
• A missing ticker symbol, CUSIP, or other identifier
• A fixed income instrument record with a null coupon value
• A benchmark or index that is missing a dividend notice or stock split
• A record with missing attributes
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Conformity
Definition A measurement of the alignment of content with the required standards.

Description Conformity measures how well the data aligns to internal, external or industry-wide standards.
Conformity is one of the seven Data Quality Dimensions.

Examples:
• Invalid ISO currency codes
• Violation of allowable values (i.e. a state code for a country that does not have states)
• Inconsistent date formats
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 Consistency
Definition A measurement of compliance with required formats, values or definitions.

Description Consistency provides assurance that data values, formats and definitions in one population
agree with those in another data population

Consistency is one of the seven Data Quality Dimensions.

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Coverage
Definition A measurement of the availability of required data records.

Description Coverage refers to the breadth, depth and availability of data that exists but is missing from a
data provider. Coverage is one of the seven Data Quality Dimensions.

Examples:
• A group of securities (i.e.: corporate bonds) not included in a vendor feed
• Quoted prices from an emerging market that are missing
• Legal entity and hierarchy data missing from a country or region
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Data Harmonization
Definition The process of aligning all representations of data to precise and consistent meaning.
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Data Normalization
Definition The process of aligning data to its defined parameters.

Description This is a business centric perspective and not to be confused with the process of
normalization in a data modeling context.
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 Data Profiling
Definition The process of evaluating and grading a given source of data to determine whether it is fit for
its intended purpose.

Description Profiling is a methodology for determining the current state of data quality in a repository.
Data profiling would include a review against all data quality dimensions to identify data
anomalies and evaluate data variance.

Synonyms • Data Quality analysis

• Data quality assessment
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Data Quality
Definition A measurement of qualitative and quantitative conditions that determine whether the data is
fit for its intended use in a business process or operation.

Description The quality of data can be evaluated against defined dimensions (i.e. accuracy, completeness,
conformity to standards, consistency, coverage, timeliness and uniqueness) as well as against
the business processes associated with its production.
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Data Quality Decay Rate

Definition The rate that a data attribute loses its level of quality over time if not maintained. Decay can
be measured against all dimension of data quality.
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Data Quality Dimensions

Definition Categories of measurement used to evaluate the degree to which data is fit for its intended
purpose.

Description The EDM Council recognizes the meaning of seven core dimensions used to define and
measure the quality of data.
The seven dimensions include:
• Accuracy
• Completeness
• Conformity
• Consistency
• Coverage
• Timeliness
• Uniqueness
Synonyms Dimension of Quality
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 Data Quality Rule
Definition Defined and documented criteria for measuring whether data is fit for its intended purpose.
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Data Transformation
Definition The process of converting the meaning and format of data from one system to another.
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Exception Handling
Definition A process by which records are catalogued, queued and remediated after failing a data quality
rule.
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Timeliness
Definition A measurement of the degree to which data is both representative of current conditions and
available for use.

Description Timeliness is a measurement of how well content represents current market/business

conditions as well as whether the data is functionally available when needed. Timeliness is
one of the seven Data Quality Dimensions.

Examples:
• A file delivered too late for a business process or operation
• An issuance or corporate action not delivered when it was announced
• A credit rating change not updated on the day if was issued
• A new prospectus not given an official number from the national numbering agency
Send feedback on this term

Uniqueness
Definition A measurement of the degree that no record or attribute is recorded more than once.

Description Uniqueness refers to the singularity of records and or attributes. The objective is a single
(unique) recording of data. Uniqueness is one of the seven Data Quality Dimensions.

Examples:
• Two instances of the same security with different identifiers or spellings
• A preferred share represented as both an equity and debt object in the same database
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For More Information
For questions about the Data Management Glossary,
to provide comments, or to inquire about membership programs,
please contact the EDM Council.

UK Main Office: + 44 (0) 208 399 7189

US Main Office: +1 (301) 933 2945

info@edmcouncil.org

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