Tutorials and Afternoon Conference Sessions
December 4, 2017

Monday
December 4
8:30-11:45

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In this introductory tutorial we provide an overview of the policies, practices, and roles associated with initiating a data governance program, as well as methods for defining and presenting metrics for management and sustainability. An effective data governance demands practices and techniques for establishing the corporate value proposition for data governance, defining and approving data policies, putting those policies into production., and ensuring that the policies continue to be observed.

This requires effective communication of data policies and associated guidance across line-of-business boundaries, as well as repeatable processes for organizing data requirements for all key data concepts across the organization. Assessing the breadth of data requirements and expectations from across the line of business landscape is key, as is ensuring consistent observance of those requirements through the design, development, and implementation phases of the system development life cycle.

In this tutorial we will also look at some practical operational aspects of data governance and stewardship, such as documenting data standards, harmonizing business term definitions and semantics, and methods for monitoring of observance to data expectations.

Attendees will learn about:

• Drivers for data governance
• Organizational operating model for data governance
• Roles and responsibilities
• Collecting data requirements
• Processes for defining and approving data policies
• Oversight of common reference data concepts
• Defining measurable metrics
• Operational data stewardship
• Data governance reporting

Level of Audience:
Introductory

Monday
December 4
8:30-11:45

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If you believe information is truly an asset, then engaging the entire business is mandatory. If managing information assets is a business issue, then data governance is a business program. Research shows none of the critical success factors for data governance have anything to do with technology. It is a key success factor that DG is aimed at providing business results, not IT results. It is also a proven fact that strong sponsorship is crucial for the success of any transformation in an organization, and EIM and DG is no different. Because so many DG programs are being initiated by business demand many participants and stakeholders find themselves in new territory.

When business leaders are called upon to "do governance,", they need to learn about concepts like stewardship, data quality, culture change and information management, all while still accomplishing their day-to-day responsibilities.

This tutorial will walk the attendees through the assessment, definition, design and deployment of a data governance program from a business view. This presentation is intended for business leaders or managers that are new to data governance, or for data governance functions that are having trouble sustaining themselves.

The tutorial will cover:

• How to define Data Governance as a business program – from alignment to operations
• How to address the most critical success factors for DG
• Understand the basic core functions that MUST be executed to be sustainable
• The differences in the business view of a DG program from an IT view
• A series of activities to pivot from a sponsorship to leadership model
• An example scenario of moving from business sponsored to “business led“
• Review a list of key metrics you can deliver immediately to show progress and success

Level of Audience:
Intermediate

Monday
December 4
8:30-11:45

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• Defining data taxonomies
• Writing good business definitions
• Dealing with multiple definitions for the same business term (e.g., customer)
• Developing workflows such as add/modify business term
• Certifying business terms
• Identifying Critical Data elements
• Adding custom attributes in the business glossary such as example and calculation
• Adding custom relations such as between report and business term
• Adding custom assets such risk model and data sharing agreement
• Alignment with data governance tools

Level of Audience:
Intermediate

Monday
December 4
12:00–12:30

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Level of Audience:
All Levels

Monday
December 4
12:00–12:30

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Prolifics will share specific client scenarios where their resulting healthy MDM solutions were built on thoughtful work to understand the data’s true potential, prepare the data, and establish effective long term governance procedures. We will share examples from the financial services and hospitality industries.

Level of Audience:
All Levels

Monday
December 4
1:30–4:45

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This tutorial explores ways to link data policies to the organization’s business goals as a way of minimizing the risks of diminished effectiveness or even outright failure. By examining the different types of data policies that must be managed as part of a data governance activity, we provide a framework for connecting data management to business needs. We then discuss ways of distilling business policies from business objectives, identifying data dependencies, defining business-relevant data policies, methods of data policy compliance, and ways that tools support data policy enforcement.

Attendees will learn about:

• Classification of data policies
• Isolating business policies and defining data policies
• Linking data dependencies to business policy compliance
• Data policy compliance
• Technologies supporting data governance

Level of Audience:
Introductory

Monday
December 4
1:30–4:45

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In this session, we will discuss how to identify what may be taxing your data governance program and how to lessen the strain. We will also explore ways to strengthen your program to be more sustainable going forward.

In this tutorial, we will share:

• Warning signs that your program is losing steam
• Key factors that affect sustainability
• Ways to get a declining program back on track
• Alternative ways to position data governance to drive interest

Level of Audience:
Advanced

Monday
December 4
1:30–4:45

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Topics that will be covered include:

• Overview of DG Program concepts to set the stage for tracking and reporting DG metrics
• Engaging the Data Governance Council and identifying business approvers for metrics
• Techniques used to identify and quantify business value
• Determining business value categories
• Assigning business value status criteria ranges
• Determining business value calculations
• Generating the business values to populate a dashboard
• Resolving data issues/errors that are identified
• Tracking potential versus actual business value

Level of Audience:
Introductory

Monday
December 4
5:00–5:45

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Data governance is the universal approach to managing and securing data in organizations. However, it isn't a one-size-fits-all solution. Local public sector agencies are regulated by federal rules, state laws and industry regulations. In addition, these agencies are multifaceted: collecting data on roads and bridges, law enforcement and corrections, energy and environment, licensing and properties, social and protection services, and libraries. These factors create distinct challenges to implementing a data governance program.

In this session, Kristi Lahti-Johnson, Data Governance Officer and Responsible Authority for Hennepin County, MN, will share how the Hennepin County Data Governance Team navigates the unique challenges local governments face in respect to protecting data privacy, ensuring compliance with federal and state regulations, and building a culture in which staff know how to manage data responsibly.

Topics include:

• Policies and procedures - balancing the individual privacy rights of our residents, the public's right to know about their government, and the government's need for and use of the data to do its work

• Large and complex agency - implementing a data governance program across 30 diverse departments that don't always speak the same language

• Change management challenges - team of six staff works to engage and educate over 7,000 employees

• Resource constraints - program budgets, staffing, data management knowledge

• Lessons learned

Level of Audience:
Introductory

Monday
December 4
5:00–5:45

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This case study explores the appropriate business, technical, and process metadata that should be required in a cloud-based data lake. Learn how these data governance components data quality, security, access and lineage manifest themselves in cloud-based big data solutions.

Topics include:

• Security and developing appropriate access and controls to the environment
• Modifying governance policies crafted for traditional RDBMS solutions to a Cloud-based, Big Data environment
• Determining  acceptable levels of data quality in this new environment
• Ensuring that performance was not impeded by the data governance process

Level of Audience:
Intermediate

Monday
December 4
5:00–5:45

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This case study is a fresh approach on how selling data governance is key to building the momentum to inspire and influence stakeholders to support a multi-year customer data strategy.

Learn how our approach includes simple words to remind strategists that innovative ideas can be accomplished by proper timing and messaging.

• Big Picture
  Understand and be able to articulate the big picture and business value of where you need to be to remain relevant and competitive in the changing customer-centric environment.

• Right Sizing
  Approach the big picture by right-sizing the effort to obtain the necessary support and funding with limited risk to your organization.

• Faster Wins
  Accomplish quicker wins by leveraging tools, processes and resources that your organization has already invested in to deepen the support and funding needed to realize a multi-year strategy

Level of Audience:
Introductory