The Five Pillars of Data Governance 2.0 Success

The Five Pillars of Data Governance 2.0 ReadinessA D A T A V E R S I T Y W E B I N A R

March 8, 2018

Today’s Speakers

© 2018 erwin. All rights reserved. 2

Mariann McDonaghCMO, erwin Inc.

Jamie KnowlesProduct Director, erwin Inc.

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

https://www.linkedin.com/in/jamieknowlesltd/@mcdonaghmariann

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

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

Our Agenda

© 2018 erwin, Inc. All rights reserved. 3

Highlights of erwin State of DG Report/research

Assessing your readiness: what

matters most

Getting there from wherever

you are

erwin’s Take on the State of DG

Traditional DG has failed.

Successful DG requires a different approach that empowers the enterprise.

Readiness is key to success.

DG should be measured and measurable in the context of the business.

DG accomplishes regulatory compliance and so much more.


Enterprise Data Governance Experience (EDGE)

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RegulatoryPeace Of Mind

VisibilityAcross Domains

IntegratedEcosystem

Any DataAnywhere

Collaboration& OrganizationalEmpowerment

Fuel Organizational Success Across the Board

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ImprovedDecision-Making

IncreasedCustomer

Satisfaction

Compliance,Privacy & Security

OperationalEfficiency

Revenue Growth

erwin State of Data Governance Report


• Surveyed North American companies in 16+ sectors, including financial services, government, healthcare, IT and telecommunications

• Respondents included CIOs, CTOs, data center managers, IT staff and consultants

In partnership with

Our customers have told us data governance is at the heart of their initiatives.

We wanted to confirm that customer feedback and gather more information from the larger market.

We wanted to understand who owns data governance, what is driving their interest, why they are making their decisions, and how they are using their data assets.

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Why Commission a Survey?

© 2018 erwin, Inc. All rights reserved.

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Key Findings

DEFINITIONS ABOUND

But it’s clear organizations are coming at data governance from many different angles.


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Key Findings

A CONTRADICTION IN TERMS

98% of respondents view data governance as either important or very important from a business perspective. However, a disquieting 46% don’t have a formal governance strategy.


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Key Findings

DO WE EVEN HAVE A BUDGET FOR THAT?More than one in five (21%) are just getting started, meaning they’re in the data discovery and inventory phase, and 63% either don’t have a budget for data governance or don’t know if they do.


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Key Findings

WHERE IS THE ENTERPRISE IN ALL OF THIS?

At 40% of the organizations surveyed, the IT department continues to foot the bill for data governance expenses.


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Key Findings

OBJECTS IN MIRROR ARE CLOSER THAN THEY APPEAROnly 6% of enterprises are prepared for GDPR, with less than four months until the regulation goes into effect.


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Key Findings

WHO’S IN CHARGE?


57% say both IT and the business are responsible for data governance, yet 68% say the CIO is driving the process.

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Key Findings

DG ISN’T JUST FOR COMPLIANCE ANYMORE

60% say regulatory compliance is the biggest driver, but it’s not the only one. 49% see it as a way to improve customer satisfaction, and 45% see it supporting better decision-making. Reputation management (30%), analytics (27%) and Big Data (22%) are also key drivers.


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Key Findings

ROADBLOCKS58% of respondents report the biggest obstacle is the cost of data governance, followed by understanding the right approach (42%), executive support (42%); organizational support (39%), effective tools (36%) and articulating business justification (27%).


Quick Poll … How ready are you?

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Category 1 Category 2 Category 3 Category 4 Category 5


1. Laggard. Have not even begun a DG project in our business

2. Novice. We have a strategy and are just beginning to assemble a team

3. Leader. We have a comprehensive DG strategy that is enterprise wide, its resourced and funded

Advice on ReadinessK E Y T H I N G S T O C O N S I D E R

Pillars of DG Readiness

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• Initiative Sponsorship

• Organizational Support

• Team Resources

• Enterprise Data Management Methodology

• Delivery Capability


Initiative Sponsorship

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GET REAL WITH EXPECTATIONS

Realistic expectations are needed, or the data governance team won’t be able to deliver against expectations. The initiative is likely to fail and be abandoned.

SPONSORS ARE KEYWithout executive sponsorship, your initiative will have difficulty obtaining the funding, resources, support and alignment necessary for successful implementation.

ENGAGEMENT MATTERS

If your sponsors are passive or only figureheads, you should consider ways to increase their involvement or solicit additional sponsors.


Organizational Support

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LEARN FROM OTHERS

Definitions should be based on industry standards and accepted best practices to ensure the initiative is based on sound fundamentals.

LONG-TERM FUNDING IS ESSENTIAL

Data governance requires continued funding, which should come from the enterprise, not be project-based.

IT’S A CULTURE SHIFT

Data governance must be integrated into the company’s current culture.

IT HAS TO BE MEASURED TO COUNT

Scope and success factors should be defined to establish parameters and metrics for evaluation.


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RELATIONSHIP

Understanding the relationship between data management and data governance is key. data management are supported by these programs.

EXPERIENCE

Most organizations lack enterprise-level DG experience, which is required to advance organizational goals.

TEAM


Most successful organizations have established a formal data management group that resides at the enterprise level because it recognizes the need for managing data as an enterprise asset.

Team Resources

IT’S VIEW

IT must be an active participant in any DG initiative, since IT is the main technical enabler of successful data governance.

Enterprise Data Management Methodology

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GET META

Metadata management provides every organization with contextual information concerning data assets.

BI

COMPONENTS TO SUCCESS MDMMDM benefits from DG because of governing common and reference data across the organization with cross-departmental standards and definitions, allowing data sharing and reuse, reducing data redundancy and storage, avoiding data errors due to incorrect choices or duplications, and supporting data quality and analytics.


DG is a foundational component of enterprise data management. It and metadata management, enterprise data architecture, data quality management, etc., are essential to success.

BI/analytics benefit from DG due to the ability to govern data from its sources to destinations in warehouses/marts, defining standards for data across those stages, and promoting common algorithms and calculations where appropriate.

Delivery Capability

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DATA MODELING

Enterprise data modeling, a component of enterprise data architecture, is an enabling force in the performance of data management and successful DG.

EFFECTIVE TOOLS

DG requires a specific tool suite. Selecting the proper DG solution should be done as part of the development of technical requirements for the DG initiative.

DATA QUALITY

Solution selections, including those for data quality management, should be based on the organization’s business goals, its current state of data quality and the rest of enterprise data management, and best practices as promoted by the data quality management team.

FORMAL DG UNIT

Having the capability to manage all DG operations and coordinate data stewardship activities can have a positive effect by giving the DG initiative administrative support for program management.


Final Poll: Any change to your earlier answer on readiness?

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Category 1 Category 2 Category 3 Category 4 Category 5


1. No change to my assessment of our readiness.

2. Food for thought. We need to consider some of these issues

What Should Organizations Look for in DG Technology?


Understand

Data Dictionary

Data Quality

Data Usage

Discover

Reference Data

Business Glossary

Socialize

Data Sets

Data Issues

Impact & Lineage

Govern

Policies and Rules

DGOM Collaboration

Workflow Collaboration Shared Services Integration

The erwin EDGE Platform

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Data Governance: The Driving Principle

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UNDERSTANDDISCOVER

SOCIALIZE

Data Sets

Data Issues

Impact & Lineage

GOVERN

Policies and Rules

DGOM Collaboration

Data Dictionary

Data Quality

Data Usage

Reference Data

Business Glossary

D ATA V I S I B I L I T Y, C O N T R O L & C O L L A B O R AT I O N U N L O C K B U S I N E S S VA L U E

What do we have? What does it mean?

Where did it come from? Is it secure? What rules or

restrictions apply?

How accurate is it?

Who is accountable?

Who is using it?

How is it used? How can I access it? Where is it?

DATA IN CONTEXT

Take the Next Step: Visit erwin.com

© 2018 erwin. All rights reserved.

Download our ebook

Request the report

https://erwin.com/white-papers/data-governance-everyones-business/?cat=erwin-expert-blog

http://go.erwin.com/2018-state-of-data-governance-report

Coming Soon: erwin DG RediChek™


No Buts About It …

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DG must align with your unique organizational goals.

What’s driving your DG program, and where do you start?

erwin understands data and how to govern it.

Real-world DG requires a cultural shift.

Our platform creates an EDGE for measurable outcomes.

Let erwin be your guide in all this.

e r w i n . t h e d a t a g o v e r n a n c e c o m p a n y .

Q&A