Conference Sessions
December 4, 2018

Tuesday
December 4
7:45–8:30

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In supporting our vision, we have established a formal framework to be the primary, authoritative resource for data governance practices. This framework, the DGPO CAP (Core Areas of Practice), unofficially referred to as the DGPO Hexy and sometimes referred to affectionately as the “Sexy Hexy” (because we know that being a data governance professional is really the sexiest job around – no offense data scientists), represents the six core areas of practice and is the foundation for all the content and best practices the DGPO will continue to share going forward.

Join us as we discuss these six practices and how they are core to all data governance programs regardless of industry, size, or maturity.

What you will learn:

1. Fundamentals – The foundational elements necessary for any data governance program.
2. Organization – Organizational considerations for data governance, both within and external to the data governance program.
3. Communication – Marketing the purpose (and general existence) of your data governance program, sharing wins and payback, and providing regular status reports. It also covers training and development and change management.
4. Process -- From documenting parameter-establishing guidelines to the detailed steps of tactical execution, the process area of practice covers the “Why, What, and How” of data governance.
5. Metrics – Metrics and measures necessary for continual improvement across the business and for communicating where the business has been, where it is now, and where it is headed.
6. Stewardship – From business to technical stewards and even data custodians, this practice area helps to define who they are and what they do.

Level of Audience
All Levels

THIS SESSION IS OPEN TO ALL CONFERENCE ATTENDEES

Tuesday
December 4
8:40–8:45

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Tuesday
December 4
8:45–9:30

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In this keynote, Kelle will provide insights for the approaches, concerns and trends that will drive information management strategies in the year ahead, including: why cloud solutions are truly the new normal; the growing importance of data privacy and ethics; the criticality of metadata and its governance; and how governance’s overall scope must be broader than “just data" (e.g. models and analytics) and be scalable for operationalization.

Level of Audience:
All levels

Tuesday
December 4
9:30–10:00

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Level of Audience:
All levels

Tuesday
December 4
10:30–11:15

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This session will showcase a model to implement data projects within your organization and how to, as a data steward you can:

• Facilitate data lineage analysis
• Define data requirements (data, calculations/rules, reconciliation reports etc.)
• Support IT design (Data modeling, Solution Architecture)
• Plan and execute User-acceptance Testing
• Support post-deployment activities

You will learn to:

• Define data owner/steward/consumer roles and responsibilities
• Socialize and educate project teams
• Write effective data movement control and reconciliation requirements
• Test and implement
• Make continuous improvements to sustain

Level of Audience:
Intermediate

Tuesday
December 4
10:30–11:15

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Scripps Health initiated an enterprise data governance program to standardize and document the dashboards/reports, metrics/KPIs, extracts, Universes and glossary terms for their new electronic health record (EHR) and revenue cycle platform. Since the first go-live, they have been working with operations and IT staff to learn and apply DG processes to their areas of responsibility to optimize the data on this platform.

Specific discussion topics include:

• Gaining C-suite support
• Identifying & inventorying our official governed data assets
• Defining roles and responsibilities for asset ownership, stewardship & reporting security
• Mapping data assets and roles to data domains
• Establishing an oversight structure (DG Council, DG Office, work groups)
• Success stories with applying DG to specific data challenges (e.g., provider master data, professional billing, hospital census)
• Lessons learned & where we go next

Level of Audience:
Introductory

Tuesday
December 4
10:30–11:15

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The Finance Data Governance Team at Nationwide centralized data quality efforts across the broader Finance organization. We accomplished this without adding additional resources and with minimal IT spends. Attendees will learn what it takes to build a data quality program that provides value back to the organization.

• Clearing the Lot - identifying needs and creating capacity
• Setting the Foundation - defining the approach & creating documentation
• Building the Frame - establishing the process
• Completing the Exterior - preparing for roll-out
• Finishing Touches - increasing capabilities
• Planning for Additions - aligning strategic direction

Tuesday
December 4
10:30–11:15

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The lessons of a century-old corporation into the disciplines and culture of Data Governance is an engaging study reminiscent of the Tortoise and Hare fable.  Hertz Global Holdings began Data Governance in parallel with other Digital Transformation efforts.  Their vision was to “Manage Data as an Enterprise Asset” to ensure success with changing platforms for CRM, Fleet Operations, Customer Service and Reservation & Rentals.  Though the Hare was wanted and cheered, a nimble Tortoise is what brought lasting value to the business organization and leadership. 
This presentation will cover the year-long journey for Hertz. 

• How a Mission and Program was envisioned and championed
• Why momentum accelerated in recruiting a Data Governance Council of Senior Executives and empowering Steering Committees for critical business entities with global representation
• Where handling business & data friction points methodically across business units democratized the initiative
• When leveraging Data Owners and Data Stewards with subsequent Data initiatives gave Data Governance lasting success

This journey was about cultural challenges introducing change and then ensuring adoption of decisions that frequently shifted the course of business strategy.  Data Governance succeeded because corporate leadership and associates alike wanted change and the results it promised. This case-study reviews critical junction points on how deliveries and patterns assisted a breath of enterprise applications needing Governance. 

Tuesday
December 4
11:25-11:55

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Level of Audience:
All Levels

Tuesday
December 4
11:25-11:55

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Level of Audience:
All Levels

Tuesday
December 4
11:25-11:55

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Level of Audience:
All Levels

Tuesday
December 4
1:00–1:45

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Monitoring Governance is a tool agnostic data driven program.

Monitoring Governance ensures:

• Minimum monitoring and alerting standards are consistently applied across all software applications and reports any non-compliance using automated non-intrusive collection methods built using open source tools.

• Our Monitoring and Alerting systems and services are being used as intended.

• The collection of monitoring data/metrics across a variety of monitoring tools and different stacks starting from Cloud Infrastructure monitoring tools, Application Performance Monitoring, Log Ingestion platforms all the way to Customer transactions, all of which are spread across multiple lines of businesses.

We have established policies and guidelines to enable consistent usage to achieve reduced maintenance costs, maximize quality and integrity of critical information

Level of Audience:
Intermediate

Tuesday
December 4
1:00–1:45

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• Not all data is created equal
• Overcoming challenges with world-wide scientific data
• How to get govern data that has changed over 200 years
• Can we speed up our product development through fundamentals of data governance?
• Setting up a data governance effort via different methods in order to coordinate with software development

Level of Audience:
Intermediate

Tuesday
December 4
1:00–1:45

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• Write a simple and easily understood data policy
• Build a corporate-wide data catalog and emphasize its importance
• Improve metadata's quality
• Define data domains and chosen data owners
• Define the main duty of each data steward role
• Establish a good neighborhood policy with the Data Security Office and Compliance teams
• Simplify data access procedures and policy

Build a data quality scorecard main topics will be:

• Implementing a corporate-wide data governance program: Top-Down vs. Collaborative approach
• Lessons learned from a former IT-centered strategy
• Data users and data steward buy-in and commitment
• Data governance and data stewardship: a roadmap

Level of Audience:
All Levels

Tuesday
December 4
1:00–1:45

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Attendees will learn:

• The overall processes for governing data policies and procedures at D&B
  
  
• What the role of Policy Functional Owner is, and how they carry out their responsibilities
  
  
• How stakeholders across the company interact with data policies and procedures
  
  
• How Enterprise Data Governance oversees the policy life cycle, ensures it is working smoothly, and informs all stakeholders who need to know about policy changes

Level of Audience:
Intermediate

Tuesday
December 4
2:00–2:30

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• Executive Support
• IT Support
• A Coordinated Approach with a Formalized Team
• Sufficient Resources and Authority
• Organizational Training & Socialization

In this keynote session, we’ll review our industry research, The State of Data Governance 2018, and the 5 Pillars of DG Readiness gleaned from this report, help attendees evaluate their organization’s readiness for Data Governance based on the success factors described above.

Level of Audience:
All Levels

Tuesday
December 4
2:40–3:10

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Level of Audience:
All Levels

Tuesday
December 4
2:40–3:10

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Level of Audience:
All Levels

Tuesday
December 4
4:00–4:45

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Level of Audience:
Introductory

Tuesday
December 4
4:00–4:45

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Data Governance is a multi-faceted discipline often perceived as nebulous and academic rather than action oriented. Because ERP implementations are costly and complex, there is a fear that data governance will only hinder progress and compromise deadlines. It is essential that data governance teams take a tactical approach to inserting governance. First, the data governance team must provide a clear vision of what robust governance looks like and the value that it brings. Then, they must clearly define the tasks necessary to materialize that vision. These activities will span key activities such as data conversion, system design, and report creation and will include overall support related to stakeholder identification and data conflict resolution.

This presentation will outline Booz Allen Hamilton's approach to:

• Obtaining buy-in and sharing responsibility for data governance
• Project lifecycle data governance activity roadmap
• Data Governance deliverables
• Leveraging project framework for enterprise-wide maturity

Level of Audience:
Intermediate

Tuesday
December 4
4:00–4:45

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Level of Audience:
Introductory

Tuesday
December 4
4:00–4:45

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Reference data – often simply known as codes, lookups, or domains – is an area of enterprise data management that is becoming increasingly important.   However, many enterprises have difficulty formulating governance programs and management practices for reference data.  This presentation explains the overall structure needed for both reference data governance and reference data management.  The options for environments for producing and distributing reference data are compared and contrasted.  The significant role of semantics in reference data is also examined in detail, together with practical ways in which knowledge of reference data can be successfully managed. 

Attendees will learn:

• What reference data is, how it differs from other classes of data in its governance and management needs
• The structures needed for successful reference data governance management
• How the semantic needs of reference data can be addressed
• How reference data is produced and distributed

Level of Audience:
Introductory