State of Data Governance in 2021

The State of Data Governance
MAY 6, 2021

Speakers
Danny Sandwell
Danny has more than 25 years of experience in the
IT industry and has been an erwin brand advocate
for 16 years. His expertise comes from various roles
in data administration, database design, business
intelligence, metadata management and application
development.
Product Marketing Manager
Mike Leone leads coverage of data platforms,
analytics, and artificial intelligence at ESG. Mike
draws upon his enthusiasm for bleeding edge
technology as well as his engineering and marketing
backgrounds to help enterprise technology vendors
improve everything from go-to-market strategies to
product development.
Mike Leone
Senior Analyst
2

Always Aim Ahead of a
Moving Target!!! ☺
Commission a study of IT and
business professionals
Explore data governance drivers, program
maturity and challenges
Establish thought leadership within the
market and determine how to help customers
3

2018 Data Governance Drivers
(research in Nov/Dec 2017)
Reputation management and analytics
rounded out the top 5
60% said regulatory compliance is
the biggest driver, but it’s not
the only one …
49% saw it as a way to improve
customer satisfaction
45% thought it would support better
decision-making
4

2020 Data Governance Drivers
(research in Nov/Dec 2019)
What are the top three drivers of your data governance/
data intelligence initiative? [Please select three choices]
Better decision-making (62%)
Analytics (51%)
Regulatory compliance (48%)
Digital transformation (37%)
Data standards/uniformity (36%)
5

Partnered with Enterprise Strategy Group
Based on responses from 220 business and IT professionals
participating in this year’s study, which took place in March.
Survey participants are from North American companies with more
than 1,000 employees and in excess of $100 million in revenue
2021 Research
Universal implications
6

Data Transformation Is Well Underway
31%
34%
35%
43%
41%
49%
20%
17%
14%
4%
5%
2%
2%
3%
To make the most of our data, we need to dramatically improve the
performance of our underlying infrastructure
If my company does not continue to find new ways to use data to
proactively customize products/offers for customers, we will be
disrupted by competitors that do
Our data represents the best opportunity for my organization to
develop a competitive advantage over the next 12-24 months
Strongly agree Agree Neutral Disagree Strongly disagree
Please rate your level of agreement with the following statements: (Percent of respondents, N=220)
7

Defining Data Governance
30%
32%
38%
48%
53%
54%
56%
56%
62%
64%
Understanding ETL operations and the mapping in them
Business intelligence self-service
Building a business glossary of data standards
Understanding deployed data in terms of ensuring it can be understood in context to
the business
Building a framework of people and processes that have responsibilities for data
Understanding data flows across the organization
Understanding deployed data in terms of sensitivity and/or regulatory requirements
Understanding data quality
Ensuring data usage follows defined rules
Building a set of policies that governs the organization around data
How does your organization define data governance? (Percent of respondents, N=220, multiple responses accepted)
8

Data Governance Maturity
42%
45%
8% 5%
Fully implemented: Data governance
is a core organizational capability; we
have a dedicated staff and formal
implementation oversight and
processes for continuous
improvement
Work in progress: We have
completed data discovery and are
developing processes, business rules,
data deﬁnitions, data classiﬁcation,
and policies for data governance
Getting started: We have begun doing
data discovery and data inventories
for governance
Planning stage: We plan to start a
formal data governance program
soon
How mature is your organization’s data governance program, or what stage are you in? (Percent of respondents, N=220)
9

Integration
Across the Data
Lifecycle Today
19%
23%
28%
28%
30%
32%
33%
35%
46%
46%
50%
54%
56%
62%
Non-relational databases
Data pipeline management
Metadata management
Data lakes
Embedded analytics
Data science platforms
Data streaming/streaming analytics
Relational databases
Data integration/data engineering
Data and systems performance
monitoring
Business intelligence
Data warehouse
Data protection
Data processing
What data-centric technologies
are integrated within your
organization’s data governance
program today?
(Percent of respondents, N=210,
multiple responses accepted)
10

Data
Governance
Drivers
6%
9%
10%
13%
20%
20%
23%
27%
34%
35%
45%
48%
Increase precision of language
Enable data self-service
Improve reputation management
Reduce colliding policies and processes for data
management
Support digital transformation initiatives
Create data standards uniformity
Increase customer trust/satisfaction
Support better decision-making
Maintain regulatory compliance
Improve analytics
Improve data quality
Improve data security
By persona:
IT (55%) vs.
LoB (36%)
By persona: IT (18%) vs. LoB (31%)
What are the top drivers of your
program (i.e., what are the top
outcomes it hopes to achieve)?
(Percent of respondents, N=220, three
responses accepted)
11

Data Value Chain Bottlenecks
29%
32%
37%
39%
40%
40%
43%
44%
Curating assets with business context
Conducting impact analysis
Synthesizing disparate data sources to serve the use
case/hypothesis
Visibility into mechanisms to protect data
Documenting complete data lineage
System performance where data is stored
Finding, identifying and harvesting data assets
Understanding the quality of source data
What are the most serious bottlenecks in your organization’s data value chain?
(Percent of respondents, N=220, multiple responses accepted)
12

Time Spent
Throughout the
Data Lifecycle
15%
19%
20%
23%
23%
Preparing data
Managing data
Searching for data
Protecting data
Analyzing data
Consider your time allocated for
the following data-related
activities. Please rank these
activities from “1 – where you
spend the most time” to “5 –
where you spend the least
time.” (Percent of respondents, N=220,
percent ranked #1 displayed)
13

22%
25%
34%
34%
38%
39%
40%
47%
54%
55%
3%
4%
9%
9%
7%
6%
4%
14%
27%
17%
Code generation and orchestration
Data lineage
Data harvesting
Impact analysis
Data cataloging
Data mapping
Data replication
Data preparation
Data quality
Data integration
Automated data operation saved the most
time (N=200, one response accepted)
Automated data operations (N=204, multiple
responses accepted)
Automation
Across the
Data Lifecycle
Which of the following data
operations has your
organization automated? Which
automated data operation has
saved individuals at your
organization the most time?
(Percent of respondents)
14

Organizations Need Better and More Comprehensive Data Visibility
45%
48%
74%
85%
52%
50%
25%
15%
3%
2%
2%
It is hard for us to determine the right level of data accessibility and
availability based on role
Users struggle with a lack of business context when accessing and/or
analyzing data
We need to better formalize data quality requirements
We monitor databases and other data systems as part of our data
governance
Yes No Don’t know
Which of the following statements do you feel applies to your organization? (Percent of respondents, N=220)
15

From the time a business user (e.g., developer, analyst, data scientist) requests data, how much time typically goes
by before that user has access to the data they need? When you request data from IT, how much time typically goes
by before you receive access to the data you need? (Percent of respondents)
Data Accessibility
8%
32% 33%
17%
4% 4% 0%
2%
22%
20%
28%
18%
6%
3%
1% 1%
Less than 4 hours 4 to less than 8
hours
1 to 2 business
days
3 to 4 business
days
1 to 2 weeks 3 to 4 weeks More than a month Don’t know
IT respondents (N=132) Business respondents (N=88)
Estimated mean: 2.4 days Estimated mean: 2.6 days
16

Self-Service Is
More Important
than Ever
Yes – we have this
capability today,
42%
Yes – we are
planning/developin
g this capability
today, 51%
No, 4%
Don’t know, 4%
LoB respondents
say time-to-data
access is ~1
business day
faster at these
organizations
Is your organization working on
self-service data provisioning for
business users (i.e., a self-
service portal where users can
define, provision and access
data without needing to involve
an IT stakeholder)?
(Percent of respondents, N=220)
17

Data Protection
Definitions are
Evolving
12%
31%
31%
31%
38%
40%
41%
50%
55%
80%
Snapshots
Archiving
Policy management
Endpoint management
Recovery
Audit and compliance
Access management
Backup
Data governance
Data security
Which of the following do you
most closely associate with the
term “data protection?”
(Percent of respondents, N=220, multiple
responses accepted)
18

Completely,
34%
Mostly, 48%
Somewhat,
16%
Minimally,
1%
Organizations
Are Aligning
Governance
and Protection 82% of
organizations
have a high
degree of
alignment
between data
protection and
governance
strategies.
To what extent is your
organization’s data protection
strategy aligned with your
strategy? (Percent of respondents, N=220)
19

Insights & Implications
Data governance is a
top priority for most
organizations, but it
has no standard
definition. Understand
your organization’s
what and why for DG.
No such thing as “fully
implemented,” or
totally mature. DG
must be sustainable,
scalable and adaptive.
Primary data
governance drivers have
remained consistent, but
more focus is on data
security and quality.
Data governance and
data quality are
intertwined.
DG challenges and
bottlenecks are
inevitable, but creating a
DG culture as an
ongoing, strategic,
funded practice enables
them to be addressed
more easily.
20

Insights & Implications continued
Still not enough time
spent on data analysis.
Significant opportunities
to automate data
operations remain to
also help with specific
bottlenecks.
Self-service done right
is a game-changer.
Done wrong, its value
diminishes.
Data is the differentiator
and key to
transformation in the
digital realm and
beyond. But
unseen/unused data
equals lost opportunities.
Data governance, data
operations and data
protection are
converging. Closer
alignment empowers
both IT and the
business.
21

Data Governance & Data Empowerment
Harvest Curate Govern Activate Socialize
Data governance provides visibility, automation, governance and collaboration for data
democratization.
As part of the Quest Data Empowerment Platform, data governance puts real-time, relevant, role-
based data in context in the hands of users to optimize the enterprise data capability.
22

erwin Data Intelligence
Supports both IT and business needs, delivering enterprise data
governance and facilitating enterprise collaboration.
Combine erwin Data Catalog
with erwin Data Literacy to
fuel an automated, real-time,
high-quality data pipeline.
Give all stakeholders access
to data relevant to their roles
and within a business context.
Power decision-making based
on a full inventory of reliable
information.
Standard Data Connectors
erwin Data Catalog erwin Data Literacy
AUTOMATION
erwin Data Intelligence Suite
Smart Data Connectors
23

Learn More
Visit erwin.com Request a demo of erwin Data Intelligence.
24

State of Data Governance in 2021

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