Data Management Meets Human Management - Why Words Matter

1 | © 2021 Alation, Inc. – All Rights Reserved.
The Catalog is the Platform™
Data Management Meets Human Management: Why
Words Matter

Mitesh Shah
Vice President of
Product Marketing
Greg Swygart
VP of Enterprise Data
ft. Charissa Toole, VP, Enterprise Data
Program Governance and Strategy
Bob Seiner
President
and Principal
People-first
Data Governance
Non-Invasive Approach
Dynamic Leadership

Classification: Confidential
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Fifth Third Bank
Data Management Meets Human
Management: Why Words Matter
June 2021
Confidential

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Who Am I
Greg Swygart, Vice President of Enterprise Data at Fifth Third Bank.
Greg is passionate about creating data-driven cultures within complex working environments. He has lived in
Cincinnati since he graduated from Xavier University and spends most of his free time trying to convince his
wife to go on hikes and watching Disney movies with his two daughters. Greg has spent the last 8 years
working in Data and Analytics in various industries including Customer Service, Retail, and Banking.

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Agenda
• Intro to Fifth Third Bank + Greg
• The Fifth Third Data Landscape [problem]
• What is Greg’s role in that landscape? [solution]
• What big obstacles has Greg faced?
• How has he overcome those obstacles?
• Words Matter for Data Governance
• How do you get people to change?
• ADKAR

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5/3 Bank

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Data Platform Ecosystem
Move
Abstract
Interact
Locate Data Explore / Discover / Engineer / Modeling Report & Visualize Integrate
Process
Store
Distributed/Processing Semi/Structured Unstructured
* Future State
redis
Manage
Data Warehouse Relational MPP ODS
IBM IDAA
[& OR]
Watson Studio
Data Classification
Data Quality
Data Catalog Lineage & Metadata Glossary
Batch ETL Extract/Load
Mainframe
Aurora DynamoDB S3 Store EMR
Non-EDO Managed
Deploy
Scheduling Provision
Tokenization
Obfuscation
Data
Capabilities
Axiom
Software Version Orchestration Artifacts
Virtualize Caching
Enrich
*
Mastering Data
*
Stream
*
*
Change-Data-Capture
Enrich
ETL DevOps
*
Secure File Transfer
On-Premise Cloud

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Why Data Management
The Basel Committee - initially named the Committee on Banking Regulations and Supervisory Practices - was
established to enhance financial stability by improving the quality of banking supervision worldwide, and to
serve as a forum for regular cooperation between its member countries on banking supervisory matters.
The EDM Council is the Global Association created to elevate the practice of Data Management as a business
and operational priority. The Council is the leading advocate for the development and implementation of Data
Standards, Best Practices and comprehensive Training and Certification programs.

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Current Landscape
DCAM Scoring Model
Not Initiated
Conceptual
Developmental
Achieved
Enhanced
Defined
3.5
3.3
3.2
3.3
3.3
3.4
3.1
4.3
3.8
3.5
3.9
3.7
3.9
3.7
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1.0 Strategy and Business Case
2.0 Data Program and Funding Model
3.0 Business and Data Architecture
4.0 Data and Technology Architecture
5.0 Data Quality Management
6.0 Data Governance
7.0 Data Control Environment
EDMC 2020 Benchmark Component Scores
All Financial Services Financial Services Tier 2 & 3

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Crossing the Capability Chasm
DCAM Scoring Model
Not Initiated
Conceptual
Developmental
Achieved
Enhanced
Defined
• Awareness: The Bank did not know how well we were performing with
Data Management best practices
• Strategy: Create a centralized Data Management Program to develop the
organization’s data literacy based on DCAM (People, Process, & tools)
• Desire: The Bank did not have a data driven culture
• Strategy: Make data fun and focus on Alation adoption and curation
• Knowledge: Many data consumers have not had the formal training
required to unleash analytical capabilities
• Strategy: Develop Data Management training curriculum and provide the
right processes and tools (no/low code options)
• Ability: Data consumers do not have the skills required to leverage data
• Strategy: Create scalable framework (Bei Dati) to execute Data
Management best practices across the Bank
• Reinforcement: Data consumers do not understand the value of
adopting new tools and technologies to leverage data.
• Strategy: Consistently drive business value & leverage Change
Management techniques

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FOR INTERNAL USE ONLY
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Enterprise Data Designations
Risk Aggregation Data (BCBS 239)
Policy and Standards
Execution Operational
Progress Measurement and
Quality Assessment
EDO Change Management &
Priority Data
Change Management and Priority
Existing data sets
Robust Data Management
integration with Table Top
Reviews
Measurement of Existing/ New
and Enterprise Data sets.
Agility IT Release
Data Management Operational
Bank wide
Data Management engrained in
LOB
DM Cube expanded and
available for self service to
consumers.
Phase Phase Phase
Create a scalable and efficient approach for the implementation of Data
Management Best Practices
Enterprise Data Designations
• Risk Aggregation Data (BCBS 239)
• Centralized DM Program
• Policy and Standards
• Progress Measurement and Quality
Assessment
EDO Change Management & Existing Data
• Change Management and Priority
Existing data sets
• Robust Data Management integration
with Tabletop Reviews
• Measurement of Existing/ New and
Enterprise Data sets.
Agility IT Release
• Data Management Operational Bank
wide
• Data Management engrained in LOB
• DM as an accelerator
Ideate Scale Federate
D
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e
N
o
w
L
a
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e
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Customer Feedback
& Outcome Validation
Customer Feedback
& Outcome Validation
• Integration of Data Management into Engineering DNA
• Reduce Data Management Risk
• Drive accountability and ownership of data
• Improve value of data

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Data Management – Standard of Care
DCAM guidance is at the core of our Data Tech Strategy
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+
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+
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p
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Access
Permissions
Service
Agreements
Data
Dictionary
Data
Quality
Business
Glossary
Technical
Lineage
Consumption
Lineage
Business
Process
Lineage

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FOR INTERNAL USE ONLY
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Create something Delicious
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Plain……………..When your data set is not designated as
Enterprise Data or on the roadmap for designation and
already exists in the data environment.
Specialty………. When your data set is not designated as
Enterprise Data or on the roadmap for designation and is
being newly created or modified in the data environment.
Supreme…………When your data set is designated as
Enterprise Data or on the roadmap for designation OR when
your stakeholders/ business partners have communicated
material impact of data quality to the data set.
Menu
Bei Dati

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Plain
(Existing Data)
Crust – Access Permissions
Document IT Role access information in the "Access Permissions"
section in Alation at the level (Schema/Table).
Sauce – Service Agreements
Document the data availability information in the "Service
Agreement" section of the catalog page for the level
(Schema/Table) necessary.
Cheese – Data Dictionary
Document Titles and Descriptions for Schemas/Tables/Columns
Titles should be a direct "English" translation of the table/ column
Descriptions should be of technical nature and contain
information regarding the purpose and use
200 Calories
Flavorable for age:
Existing
EDO Change
Enterprise Data

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Specialty
(Newly created
or modified data)
400 Calories
Flavorable for age:
Existing
EDO Change
Enterprise Data
Titles should be a direct "English" translation of the table/ column
Descriptions should be of technical nature and contain information
regarding the purpose and use
Meat – Data Quality
Identify current table level Data Movement controls and implement
monitoring where necessary.
Profiling Data Quality rules.
Veggies – Technical Lineage
Document Source(s) for table and columns in Alation

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800 Calories
Identify Critical Data Asset, Element criticality, Data Steward
Meat – Data Quality
Identify current table level Data Movement controls and
implement monitoring where necessary.
Profile Critical Data Elements and utilize Ataccama to write
necessary Data Quality Rules
Veggies –Lineage
Business Process – Align to business processes
Tech - Document Source(s) for table and columns in Alation and submit
manual template for system level hops of Critical Data Elements.
Consumption – Manually document the consumption of critical data
assets and critical data elements
Extra Cheese – Business Glossary
Create a Business Glossary in Alation documenting
Business Terms and align to Critical Data Elements
Well Done
Certification and QA
Flavorable for age:
Existing
EDO Change
Enterprise Data
Supreme
(Enterprise Data/
Business Critical Data)

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Data Management
Traditional Data Governance
Why Words Matter
Centralized Governance Federated Data Management
Subject Matter Experts Data Management Mavens
Governance Controls Data Handling Best Practices
Data Stewards Data Stewardship Meetings
Catalog Curation
Assign Recognize

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Change is Hard

Human Management and Non-Invasive Data Governance
What exactly are
we governing?
Data or people’s
behavior?
The data will do
what it is told!
The people’s behavior
is what needs to be
governed!
People respond to
the words that we
use to govern
behavior!

Human Management and
Non-Invasive Data Governance
Non-Invasive Data Governance Core Tenets
• “Everybody is a Data Steward. Get Over It!”
• “You are Already Governing Your Data”
• “Formalization and Activation –
Two Sides of the Same Coin”
To activate your
Data Governance Program
and Your
Data Catalog
Stay Non-Invasive
in Your Approach

Data Will Not Govern Itself
• People define, produce and use data as part of
their everyday job
• Formalize accountability rather than handing
people more work
• Use a data catalog to activate and formalize
accountability and govern data

Metadata Will Not Govern Itself
• … And some people define, produce and use
metadata as part of their everyday job
• Formalize accountability for metadata to activate
people and the data catalog
• Use a data catalog to activate and formalize
accountability and govern metadata
Recognize Metadata Stewards
for Defining, Producing and
Using Metadata in the
Data Catalog

Data Management
Best Practice & Infrastructure
Data Definition
Data Production
Data Usage
Delivery on Time –
Within Budget
Project Management
Data Management Meets Human Management
Making Data
Governance Fun
(or at least
not a burden)
Human Management
Formalized Accountability
For Data Definition
For Data Production
For Data Usage
Data Governance
Metadata Governance
Overlap
Execution &
Enforcement
Stewardship
Active Data Catalog

Activation and Enablement
Data Governance Requires That Organizations Activate People
Data Catalogs Enable Active Data Governance

What do these things have in common?
Words Matter
Formalize
Accountability
Recognize
Academic
vs Realistic
Make it Fun
It’s Not
More Work
Use Analogies

People
Words Matter
Formalize
Accountability
Recognize
Academic
vs Realistic
Make it Fun
It’s Not
More Work
Use Analogies

?

Alation takes a people-first approach
to data governance

Policies and Quality Flags
Policies and quality flags
are surfaced in the user’s workflow
vs
Emails
Documents
Word of Mouth
Policies and quality information
are scattered
Trusted Data,
Compliance

Business Glossary
Glossary terms
are suggested automatically and linked
to related physical data objects
vs
Thousands of Terms
Millions of Data Objects

Stewardship Dashboard
Stewardship dashboard
shows progress and helps prioritize curation efforts
vs
Hamster wheel

Governance Customers
And more…

Join Us!
See for yourself how Alation can turn around your data governance
initiative: Join us on June 17th for a data governance demo:
alation.com/dg-demo
Leverage active data governance with Alation. Get tips for success in
our Data Governance Methodology White Paper:
alation.com/dgm21

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