data governance 101: foundations and concepts · 2020. 7. 23. · management, metadata management...

EWSolutions

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Over 125 Successful Client Partner Implementations

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Data Governance 101:

Foundations and Concepts

Webinar Series: Data Governance Mastery

Anne Marie Smith, Ph.D.

VP of Education, Chief

Methodologist

EWSolutions

[email protected]

mailto:[email protected]





EWSolutions’ Background

EWSolutions is a Chicago-headquartered strategic partner and full life-cycle systems integrator

providing both award winning strategic consulting and full-service implementation services. This

combination affords our client partners a full range of services for any size enterprise information

management, metadata management, data governance and data warehouse/business intelligence

initiative. Our notable client partner projects have been featured in the Chicago Tribune, Federal

Computer Weekly, Journal of the American Medical Informatics Association (JAMIA), Crain’s Chicago

Business, The Doings and won the 2004 Intelligent Enterprise’s RealWare award, 2007 Excellence

in Information Integrity Award nomination, DM Review’s 2005 World Class Solutions award and 2016

CIO Review 20 Most Promising Enterprise Architecture providers.

For more information on our Strategic Consulting Services, Implementation Services, or

World-Class Training, email us at [email protected] or call at 630.920.0005

Best Business Intelligence Application

Information Integration

Client: Department of Defense

World Class

Solutions Award

Data Management

2007 Excellence in Information

Integrity Award Nomination


http://www.ewsolutions.com/news-events/news-press-releases/press_release.2005-10-03.9140171518




Over 150 Client Partners Since 1997

For more information on our Strategic Consulting Services, Implementation Services,

or World-Class Training email us at [email protected]

AFLACAON (Hewitt Associates)

Arizona Supreme CourtBank of America (Countrywide)

Bank of MontrealBankUnited

Basic American Foods

Becton, Dickinson and CompanyBlue Cross Blue Shield companies

Booz Allen HamiltonBranch Banking & Trust (BB&T)

British Petroleum (BP)

California DMVCalifornia State Fund

Canadian Institute for Health Information (CIHI)Canadian National Railway

Capella UniversityCigna

College Board

ComcastCorning Cable Systems

Contech Systems, Inc.CostCo

D.A. Davidson

Defense Logistics Agency (DLA)Delta Dental

Department of Defense (DoD)Department of State (DOS)

DiscoverDriehaus Capital Management

Eli Lilly and CompanyEnvironment Protection Agency (EPA)

ErwinFarmers Insurance Group

Federal Aviation Administration

Federal Bureau of Investigation (FBI)FedEx

Fidelity Information Services Ford Motor Company

GlaxoSmithKline

Harbor FundsHarris Bank (BMO)

The HartfordHarvard Pilgrim HealthCare

Health Care Services CorporationHP (Hewlett-Packard)

IDMA (Insurance Data Mgt. Institute)

Information Resources Inc.International Paper

IQVIA (Quintiles)Janus Mutual Funds

Johnson Controls

Key BankLiquidNet

Loyola Medical Center

SurescriptsTarget Corporation

Texas CPAThe Regence Group

Thomson Multimedia (RCA)Thrivent Financial

United Healthcare (UHC)

United Health GroupUnited Nations (ICAO)

United States Air ForceUnited States Army

United States Courts

United States Department of StateUnited States Fish and Wildlife Service

United States NavyUnited States Navy (BUPERS)

United States Transportation CommandUniversity of Michigan

University of Wisconsin Health

USAAUS Cellular

Vera BradleyWaste Management

Wells Fargo

Wisconsin Department of TransportationWorkers’ Compensation Insurance Rating Bureau of California (WCIRB)

Zurich Cantonal Bank

Manulife FinancialMayo Clinic

McDonaldsMicron

MicrosoftMoneyGram

NASA

National City Bank (PNC Financial)Nationwide

Neighborhood Health PlanNORC

Physicians Mutual Insurance

PillsburyQuartz Benefits

Rowan College of South Jersey (RCSJ)Sallie Mae

Saudi Arabia Minister of the InteriorSaudi Telecom Company (STC)

Schneider National

Secretary of Defense/LogisticsSingapore Defense Science & Technology Agency (DSTA)

Social Security AdministrationSouth Orange County Community College

Spherion

Standard Bank of South AfricaSunTrust Bank





Background – Anne Marie Smith, Ph.D.

❑ Internationally recognized expert and speaker in the fields of enterprise information

management, metadata management and data warehousing, one of the top industry

experts in data governance, and in data management strategy and planning

❑ Over 20 years experience in delivering solutions in enterprise information management

for numerous companies / clients across varied industries and governments.

❑ Published numerous articles that have been featured in some of the industry’s most

prestigious magazines and newsletters. Executive Editor and Content Manager.

❑ Contributing author and reviewer to the DAMA Data Management Body of Knowledge

(DAMA-DMBOK©)

❑ Has taught at several institutions of higher learning including LaSalle University

❑ Holds certifications in enterprise data management (CDMP), data warehousing (CBIP),

and data governance, and has earned a Ph.D. in Management Information Systems.

Also holds various industry certifications (e.g., ARM)





OVERVIEW OF ENTERPRISE DATA

MANAGEMENT

Strategic Partner & Systems IntegratorIntelligent Business Intelligencesm





Data as a Corporate Asset

❑ Data, like all corporate assets, must be managed to achieve the maximum benefit

❑ Well-managed, high-quality data supports effective decision-making and promotes improvements in information usage across the organization

❑ Poorly-managed, un-governed data can result in erroneous business decisions and compliance issues





Enterprise Data Management Definition

❑ Enterprise Data Management is the collection of functions that

coordinates all components of enterprise data management

❑ It organizes the various common activities of each component and

manages them so the organization can operate effectively and

efficiently in the management of data as an asset

➢ Manages the pieces of the data management puzzle

❑ Without enterprise data management, all the component functions

would be performed disjointedly

➢ Every successful enterprise data management initiative has a professional

data management team





DAMA-DMBOK © Framework

Data Management FunctionsEnvironmental Elements

Strategic Partner & Systems Integrator

Intelligent Business Intelligencesm





EIM Functional FrameworkD

ata

Ste

ward

sh

ip

Structured

Data

Management

Unstructured

Data

Management

Reference & Master

Data

Management

Data

Warehousing &

Business

Intelligence

Information

Quality

Management

Data Governance

Information Architecture

Metadata Management

Information Security Management

Transaction DataBusiness

Intelligence Data

Reference & Master

Data

Unstructured &

Semi-Structured

Data

EIM

Serv

ice

s

© http://www.ewsolutions.com





Alternate EIM Framework





DATA GOVERNANCE

Strategic Partner & Systems Integrator

Intelligent Business Intelligencesm





DAMA-DMBOK © Framework

Data Management FunctionsEnvironmental Elements





Understanding Data Governance

DataMisunderstood

Inaccurate

Misleading

Data Governance

Actionable Information

Understood

Accurate

Consistent

Policies, Procedures, Consensus, Knowledge,

Information, Data, Metadata

Transform

Data StewardsData Stewards

Data Governance

Professional





Data Governance & Data Stewardship

Data Governance is the function

responsible for planning, implementing,

guiding, monitoring and promoting

strategies, policies, standards and

procedures to ensure effective control and

use of an organization’s data / information

assets.

Data Stewardship is the assigned

role with accountability and

responsibilities to be trustees of

enterprise data, implementing the

decisions of data governance.





Data Governance vs. Data Stewardship

❑ Data Governance• Data management and data governance

knowledge – data governance experts

• Policies

• Practices

• Standards

• Enterprise focus

• Enterprise communication and

socialization

❑ Data Stewardship• Domain content knowledge – business

subject experts

• Domain development / implementation of

data governance policies, standards,

practices

• Domain implementation of data

governance procedures

• Socialization of data governance in

domain

• Data and metadata quality standards for

domain





Data Governance Definition

❑ Data Governance is the core function of the Enterprise Data Management Framework ➢ Data Governance is NOT the same as Enterprise Data Management

➢ Data Governance is NOT simply policies and processes

➢ Data Governance is NOT synonymous with Data Stewardship

❑ Data Governance interacts with and influences each of the other data management functions

❑ Data Governance is the function that develops and manages policies, practices, standards, and procedures for managing data and information across the organization.

An effective data governance program supports the performance of an effective enterprise data management function





Data Governance is NOT EIM

❑ Data Governance is not to be confused with Enterprise Information Management

or Data Strategy

Enterprise Information

Management (EIM)

Data Governance Data Strategy





Data Governance Goals

Define, approve, and communicate data strategies, policies,

standards, architecture, procedures, and metrics

Track and enforce conformance to data policies, standards,

architecture, and procedures

Track and enforce conformance to data policies, standards,

architecture, and procedures

Manage and resolve data related issues

Sponsor, track, and oversee the delivery of

data management projects and services

Understand and promote the value of

data assets





Data Governance Benefits❑ Enables the organization to produce high-quality information which is useful, appropriate, and

timely by:

Providing one point of accountability for

each critical attribute

Reducing data duplication

Increasing confidence in data (quality,

usage, etc.)

Improving timeliness and usability of data

Establishing a common vocabulary

of data to ensure access to the right

information

Defining common values for common

reference data (master data)

Providing information and guidance to

assist in compliance and regulatory efforts

concerning data





Common Issues for Data Governance

A Data Governance program should be used for identifying, quantifying, prioritizing, and resolving

several different types of data related issues across the organization, including:

❑ Authority: Questions regarding decisions rights and procedures for data usage and management

❑ Change management escalations: Issues arising from the change management process concerning data policies, practices, processes, standards

❑ Compliance: Issues with meeting compliance and regulatory requirements based on data

❑ Conflicts: Conflicting policies, procedures, business rules, names, definitions, standards, architecture, data ownerships and conflicting stakeholder interest in data and information

❑ Conformance: Issues related to conformance for policies, standards, architecture, and procedures

❑ Data security and identity: Privacy and confidentiality issues, including breach investigations and identification of sensitive and classified data

❑ Data quality: Detection and resolution of data quality issues, including disasters or security breaches





8 Reasons Data Governance Fails

❑ Loss of executive support – from multiple business units as well as Information Technology

❑ Lack of a proper data management foundation in organization

➢ Lack of formal data governance program office / team

➢ Lack of formal enterprise data management team

❑ No metrics – no ways to measure success

❑ Poor planning at program and project levels

❑ Loss of momentum – communication issues

❑ Loss of funding

❑ Program viewed as ‘overhead’ with no defined value

❑ Loss of key personnel in data governance and stewardship roles





Key Attributes: Successful Data Governance Programs

Adoption of Enterprise

Data Management

methodology and

standards throughout the

organization

Creation of an

enterprise data

governance

program team –

professionals in

data governance

Strong, continued

management support of

the data stewardship

teams

Continued focus on improving

data and information quality

Successful, continual

interaction among data

stewards, SMEs, and all

data management

professionals

Establishment of

measures to chart

progress of data

governance and

data stewardship





A Closer Look at Data Governance

“Data Governance is the exercise of decision-making and authority for data-related matters.”

-DAMA-DMBOK©

Definition

“Management is the decisions you make. Governanceis the structure for making them. Data Governance makes decisions about how to manage data.”

-CIO Magazine

Alternate Definition

Examples of decisions facilitated by Data Governance:

1. What is the definition of a Customer? What is a Location?

2. What is the priority of fixing addresses of our Locations?

3. Should this report come from the Data Warehouse or SAS? Why?

Data Governance guides each of the other data management functions. It is a function that

defines decision rights, practices, and accountabilities to identify who can take what

actions with what information, and when, under what circumstances, and with what methods.

Legislative:

Creates

Rules

Executive:

Provides

Services

Judicial:

Resolves Issues

Data

Governance

Data Governance processes

facilitate and balance needs of

stakeholders:

• Business & Technology

Groups

• Those who use information

• Those who make decisions

about data (e.g. Compliance,

Security)





What Does Data Governance Do? Planning

➢ Understand strategic and tactical enterprise data needs

➢ Support the enterprise data strategy

➢ Identify and appoint business data stewards

➢ Establish data governance and stewardship teams / groups

➢ Develop and approve data policies, standards and procedures

➢ Plan and support data management projects and services

➢ Estimate data asset value and associated costs

Control

➢ Supervise data management teams’ actions concerning data

➢ Coordinate data governance activities in projects and services

➢ Manage and resolve data issues

➢ Support regulatory compliance with data policies, standards, processes

➢ Monitor and enforce conformance with data policies, standards and architecture

➢ Communicate and promote the value of data assets

Data

Governance





What Does Data Governance REALLY Do?

Create and

implement data

naming and

definition

standards

Identify, create and

implement metadata

management standards

Create and

implement metrics

for data

management

monitoring

Develop data

quality

management

processes (in

conjunction

with DQ team)

Deliver education and

support change

management for data

best practices

Create and

implement principles

and policies for data

management





Value Proposition: Data Governance

Examples

• Improve profitability with better consumer analytics for improved decision making

• Improve products/service introduction with improved vendor master data

• Accelerate processes such as product development, which results in faster time to

implementation and delivery

• Identify sources of new markets, partners, customers, etc., through related data

• Improve quality of reporting to regulators and authorities; prevent fines, penalties and

sanctions; improve reputation with regulators and authorities

• Manage credit exposure risk through better access to high-quality data

• Support business continuity and disaster recovery requirements through enhanced data

management capabilities

• Reduce research time to find the right information

• Lower cost of data management and integration through enterprise data source mapping

and definitions

• Improve agility – accelerate IT projects with improved data standards

• Reduce the time and cost of decisions, based on accurate facts and data

• Improve decision making through trusted data across enterprise

• Enable optimization of processes with accurate data

• Empower business with involvement in data governance and data stewardship

• Provide common business definitions of data used across organization for clarity and improved

performance by all staff

• Reduce chance of error caused by data loss, damage, or data entry mistakes

MGI

Value

Increase Revenue

Manage Costs and

Complexity

Manage Risk

Improve

Performance Quality

ExamplesBusiness Drivers





Improved Process

EfficiencyGovernance of data

improves efficiency of

processes through

improved understanding of

data

Reduced Search TimeThrough metadata defined

by business and available

across the company

Reduced Labor and

RedundancyThrough improved data

management and business

understanding of data

Improved Data QualityMore accurate, timely,

valid, accessible, complete,

reliable data throughout the

company

Improved Decision

MakingFaster, more confident

decisions made due to

reliance on available high -

quality data

Reduced IT CostsImproved data

management reduces data

duplication and need for

redundant data sources

Improved AnalysisThrough better availability

of analytical data, with

supporting policies,

standards

Improved ComplianceDelivery of accurate,

properly governed data to

regulators and leadership

reduces compliance errors

Data Governance Typical Benefit Streams





Data Governance Cultural Change

Professional staff

on Data

Governance

Program Team

Senior staff /

leadership serving

on Data

Governance

Council

Hiring, retaining data

management and data

governance

professionals

Embedding data

governance into the

organization, through the

business

Adopting effective

data stewardship

for improved data

quality

Identifying critical success

factors, failure reasons,

business case

opportunities, and

challenges

Educating leadership and

staff on data governance,

data stewardship, and data

management best

practices





Experts’ Comments: Data Governance Program Value

Poor quality information costs organizations between 20% to 35% of their operating revenue due to process

failures and information duplication/error and rework. This number could increase up to 40% for organizations which

are information intensive, such as financial services organizations, insurance and pharmaceutical companies.”Source: Industry expert James Rouse of RES Partners

Enterprise Data Governance can realize “an average ROI of $6.12 returned for every dollar spent. 62% of all

returns come from direct benefits such as reduced conflicts with data definitions or avoidance of staff or service

bureau costs. Another 38% of returns came from indirect benefits, such as productivity.” Source: Nucleus Research Report on Data Governance

"Most companies needlessly store each data field redundantly four times. Companies that are proactive in using

their technical meta data to remove this redundancy can save at least 15 percent of their IT budget due to

storage reduction and a decrease in redundant search for data. Additional cost savings can be realized due

to improved understanding of data that has been rationalized and properly defined and used across the

organization.“ Source: David P. Marco, industry expert, author Building and Managing the Meta Data Repository





❑ Data-related business inefficiencies will be impossible to address without

adoption of enterprise data governance to improve organizational, process and

technology activities

❑ Current data management challenges directly contribute to the money that an

organization spends annually on responding to information discovery requests

and on data re-work

❑ The lack of a best practices-based data governance program will continue to

inhibit growth capabilities and will contribute to continued poor data quality and

inefficient data collection, usage, etc.

❑ The longer an organization waits, the more expensive problems will be to fix

❑ Many business projects, including analytics capabilities, have dependencies on

data governance to manage data as an enterprise asset

Why Act Now?





❑ Data Governance is a foundational function for effective enterprise data management

➢ Enterprise Data Management is more than Data Governance

➢ Without Data Governance, difficult to manage data as an asset

➢ Big Data, Data Science and Advanced Analytics all require an enterprise data governance program

❑ Data Governance and Data Stewardship are NOT synonyms

➢ Complementary, supporting, and essential

❑ Data Governance has many benefits – and many challenges

➢ Realizing benefits and overcoming challenges is a journey

Key Learning Points





Questions





EWSolutions

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Bloomingdale, IL 60108-2960

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PO Box 70

Hinsdale, IL 60522-0070

http://www.EWSolutions.com

Enterprise Warehousing Solutions, Inc.

© 2017 All Rights Reserved

Anne Marie Smith, Ph.D., CDMP

VP of Education, Chief

Methodologist

EWSolutions, Inc.

[email protected]://www.linkedin.com/in/annemariesmith

Contact



https://www.linkedin.com/in/annemariesmith




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data governance 101: foundations and concepts · 2020. 7. 23. · management, metadata management...

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