Conference Sessions and Afternoon Workshops
November 16, 2016


Wednesday
November 16
7:30–3:30
Registration
Wednesday
November 16
7:00–8:00
Continental Breakfast
8:00 - 8:50 CONCURRENT SESSIONS

Wednesday
November 16
8:00–8:50

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PANEL: Tips from the Trenches
Lessons Learned from Successful Practitioners
Moderator: Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners
Panelists:
Barbara Deemer, Chief Data Steward and VP Financial Systems, Navient
Tonya Walker, AVP, Finance Data Governance, Nationwide
Curtis Lee
, Executive Director for Data Quality, Jefferson County Schools
Samson Annamdevula, Senior Manager MDM, Horizon Blue Cross Blue Shield of NJ
HoChun Ho, Global Head of Data Governance and Management, JLL

This panel discussion will focus on real life experiences and challenges encountered by practitioners in starting, deploying and sustaining data governance and data stewardship programs.

Topics include:

  • Getting started with data governance and stewardship
  • Measuring, showing and sharing the value of your data governance program
  • How to get people involved and keep the momentum going with a data governance council
  • Proven communication methods and techniques to leverage
  • If you had to start over again what would you do differently

Level of Audience:
All Levels

Moderator:
Malcolm Chisholm Malcolm Chisholm
Chief Innovation Officer
First San Francisco Partners

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Panelists:
Barbara Deemer Barbara Deemer
Chief Data Steward and VP Financial Systems
Navient

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  Tonya Walker Tonya Walker
AVP, Finance Data Governance
Nationwide

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Curtis Lee Curtis Lee
Executive Director for Data Quality
Jefferson County Schools

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  Samson Annamdevula Samson Annamdevula
Senior Manager MDM
Horizon Blue Cross Blue Shield of NJ

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HoChun Ho HoChun Ho
Global Head of Data Governance and Management
JLL

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Wednesday
November 16
8:00–8:50

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Navy Federal Credit Union:  A Case Study in Business-Driven Reference Data Management and Governance
Leena Dalvi, Enterprise Data Strategy and Services Leader, Navy Federal Credit Union
Art Heine, Enterprise Reference Data Management Lead, Navy Federal Credit Union

Navy Federal Credit Union, a leading financial institution serving more than 6 million military members and their families, wanted to provide a higher degree of personalized services to its members by leveraging its available in-house data. Navy Federal began this journey by establishing a strong data governance and information quality program driven by the business, while building the next generation data warehouse to support enhanced analytics needs.

Not always an easy process, Navy Federal's experience is a story of strategy, culture, change management, and technology lessons.

Leena and Art will share some real-world examples of the strategies Navy Federal adopted to enhance its Reference data management and governance capabilities to better serve its members. 

The case study will include an exploration of how Navy Federal:

  • Used the DAMA functional framework for standards and guidance
  • Used data profiling to assess, document, and leverage data
  • Created Integrated Enterprise Reference Data Repository to facilitate as a Single Point of Truth by normalizing more than 100,000 codes across 12 disparate business systems
  • Drove broad involvement in Reference data management by establishing four-tier data governance
  • Leveraged business stakeholders and data stewards to collect meaningful business metadata like definitions and code descriptions.
  • Gained measurable business value from well-managed Enterprise Reference data

Level of Audience:
Introductory

Speakers:
Leena Dalvi Leena Dalvi
Enterprise Data Strategy and Services Leader
Navy Federal Credit Union

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  Art Heine Art Heine
Enterprise Reference Data Management Lead
Navy Federal Credit Union

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Wednesday
November 16
8:00–8:50

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Heading Off the Analytical Zombie Apocalypse (AZA)
Grant Sutton, Director, Solution Architecture and Data Governance, Datasource Consulting

It is a terrifying site.  In a world where the demand data insights continues to far outstrip the supply you watch helplessly as your organization plods, zombie-like, toward eventual letdown.  Swept up in wave after relentless wave of requests, your reporting and analytics teams struggle to keep up their quality work, but eventually risk becoming analysis zombies.  It's the Analytical Zombie Apocalypse (AZA), but DG can come to the rescue!

Based on real-life experience in organizations like yours, this session shows you how to enliven your reporting, analytics and metrics efforts through your Data Governance capabilities.

You can do it without machetes, shotguns or explosives.  You can also do it without adding people or technology (hence no sales pitch).  It sounds almost too good to be true, but you'll learn how other Data Governance efforts have engaged their BI brethren for a real win-win.

This represents a great candidate for an early win for a DG capability with little or no investment required.  Real how-to, related with a sense of humor.

Level of Audience:
Intermediate

Speaker:
Grant Sutton Grant Sutton
Director, Solution Architecture and Data Governance
Datasource Consulting

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8:50 - 9:20 COFFEE BREAK AND EXHIBITS
arrow9:20 - 9:50 DATA GOVERNANCE SOLUTIONS

Wednesday
November 16
9:20–9:50

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A New Breed Of Data Intelligence
John Yancey, Strategic Sales Specialist, ASG

Join ASG Technologies’ Strategic Sales Specialist John Yancey as he shows off ASG’s latest and greatest Data Intelligence solution including:

  • Proactive Data Lineage
  • Data Quality Trending
  • Enhanced Lineage Stitching

Level of Audience:
All Levels

Speaker:
John Yancey John Yancey
Strategic Sales Specialist
ASG

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Wednesday
November 16
9:20–9:50

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How to Stop Spending Your Day Fighting Data Fires and Start Adding Value
Cameron Ogden, VP Solutions Management, DATUM

With today's increasing data volumes and expanding data demands on integration across the enterprise, a data steward can quickly become overwhelmed. Do you go from data fire to data fire, constantly answering the same questions and fixing the same mistakes? Would you like more visibility into what data that matters and why? In this exciting session, Cameron Ogden will show you a simple, business-friendly platform that can help you stop the madness and become a more strategic and efficient data steward. 

Level of Audience:
All Levels

Speaker:
Cameron Ogden Cameron Odgen
VP Solutions Management
DATUM

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arrow9:50 - 10:10 ROOM CHANGE
10:10 - 11:00 CONCURRENT SESSIONS

Wednesday
November 16
10:10–11:00

 

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Challenges of Implementing Data Standards in an Account Driven Environment  
Rick Hudson, Lead of Data Management, Americas, Jones Lang LaSalle

A large account-driven real estate corporation with lots of data has the foresight to see the long term benefits of providing benchmarking and analytics for its clients and itself.   By using and marketing the use of that data, JLL is creating a leading edge business analytics platform.  Data standards are key to successful benchmarking and analytics.  However, it is one thing to determine data standards agreed upon by JLL but it is quite another to get customers to agree to and implement those standards. 

Key topics:

  • How to determine what standards to implement that should be universally accepted, regardless of industry.  Then prioritizing the implementation of those standards.
  • Determining standards that are more difficult to implement across different industries and creating solutions when inevitable deviations occur.
  • Holding the client accountable to the adopted standards and ensuring they understand the repercussions of data quality drift.
  • Understanding that most clients really want our help and are looking for guidance on how to adopt the standards but also need to know the value of the work to get there.
  • Difficulties in creating a Data Governance organization in a well-established organization and gaining acceptance from key stakeholders.
  • It's difficult but it keeps us Data Governance folks in business.

Level of Audience:
Intermediate

Speaker:
Rick Hudson Rick Hudson
Lead of Data Management, Americas
Jones Lang LaSalle

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Wednesday
November 16
10:10–11:00

 

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Data Governance for the Data Lake –
Improving Agility, Flexibility, and Value
Donna Burbank, Managing Director, Global Data Strategy, Ltd

Are you struggling with what Data Governance means in the context of the Data Lake?  Much of the promise of a Data Lake is in the flexibility, agility, and scalability it offers.  Learn how Data Governance, when properly applied to the Data Lake context, can augment its value and show maximum value to stakeholders in less time than non-governed Data Lakes.
  • To Govern or Not to Govern:  Identifying which data assets it makes sense to control (and what to leave alone)
  • Rules of Engagement:  Identifying a practical framework & operating model for the Data Lake environment
  • Stakeholder Engagement:  Working with various roles within the organization in a way that makes sense for each, from business users, to data architects, to data scientists, and more
  • Rollout & Value -   Delivering “quick wins” to the organization

Level of Audience:
Intermediate

Speaker:
Donna Burbank Donna Burbank
Managing Director
Global Data Strategy, Ltd

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Wednesday
November 16
10:10–11:00

 

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Data Naming Architecture - How to Define and Name Data According to Standards
Karen Sheridan, Data Management Senior Business Consultant, The Hartford

The Hartford has developed a repeatable data naming methodology that, when followed, results in creation of a consistent enterprise vocabulary. A standardized naming process helps to minimize redundancy and prevents the use of alias terms. Data Stewards leverage this process to create business names and definitions to load into our metadata repository via our data dictionary template.  The resulting business glossary provides the foundational building blocks for standardized and consistent data naming throughout the enterprise.  The gradual development of one name for one business concept and one piece of data enables better communication across the enterprise by both people and systems and provides users the ability to understand relationships between data elements. A good name should provide an indication of the purpose and meaning for the data without dependency on a repository.

Process:

  • Identify the Need to Define a Data Element
  • Class Words
  • Defining Data Elements
  • Defining Component Terms
  • Crafting the Master Data Name

Level of Audience
Introductory

Speaker:
Karen Sheridan Karen Sheridan
Data Management Senior Business Consultant
The Hartford

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11:00 - 11:15 ROOM CHANGE
11:15 - 12:15 

Wednesday
November 16
11:15–12:15

KEYNOTE
PANEL

 

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The Future of Data Governance
Moderator:
Danette McGilvray, President and Principal, Granite Falls
Panelists:
Sunil Soares, Founder and Managing Partner, Information Asset, LLC
Ian Rowlands, VP of Product Marketing, ASG
Rex Ahlstrom, Chief Strategy Officer, Back Office Associates
Anne Buff, Principal Business Solutions Manager, SAS

As we reflect on the past three days, what questions emerge about the coming years? What does the future of Data Governance hold?

The panel of experts will discuss the following and more:

  • What are the likely future trends for Data Governance?
  • What do the future Data Governance workforces look like within organizations?
  • What does the future hold for Big Data, Cloud Computing, Mobile Computing and the Internet of things in relation to Data Governance?

Level of Audience
All Levels

Moderator:
Danette McGilvray Danette McGilvray
President and Principal
Granite Falls

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Panelists:
Sunil Soares Sunil Soares
Founder and Managing Partner
Information Asset, LLC

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  Ian Rowlands Ian Rowlands
VP of Product Marketing
ASG

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Rex Ahlstrom Rex Ahlstrom
Chief Strategy Officer
Back Office Associates

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  Anne Buff Anne Buff
Principal Business Solutions Manager
SAS

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12:15 - 1:30 LUNCH AND EXHIBITS
1:30 - 4:45 AFTERNOON WORKSHOPS

Wednesday
November 16
1:30–4:45

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W1 - Data Governance for Successful Data Quality
Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

Data Quality is a primary practice area of Data Governance, but has many challenges.  This workshop describes what Data Governance needs to do to establish a successful enterprise-level Data Quality program.  The scope of Data Quality is described, together with Data Issue Management, which is often overlooked as a discipline that needs special attention.  Approaches to continuous Data Quality monitoring are described, especially in the context of data movement.  The use of profiling for Data Quality is examined, and the governance of Data Quality Business Rules is explored in detail.   In particular, traceability of Data Quality Business Rules, and the coordination with business glossaries and definitions is described.  Additionally, the need for governance over the metadata involved in Data Quality, and how this is factored into repositories is described.  Data Issue Management and Data Change Management are put into the context of their relationship with Data Quality and how they must all be made to fit together.

Attendees will learn:

  • How Data Governance can set the scope of Data Quality to manage expectations and plan strategy
  • What the different components of Data Quality are, and how to plan for and implement them
  • Managing Business Rules for Data Quality and how to implement them in Data Quality tools
  • The role of business users in Data Quality, and their role in Data Issue Management
  • How to report on Data Quality and how to monitor and evaluate a Data Quality Program

Level of Audience:
Intermediate

Speaker:
Malcolm Chisholm Malcolm Chisholm
Chief Innovation Officer
First San Francisco Partners

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Wednesday
November 16
1:30–4:45

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W2 - The Art and Science of Data Quality Metrics
Danette McGilvray,  President and Principal, Granite Falls
We know that a data quality monitoring process will not guarantee quality.  However, once root causes are identified, measures to prevent data quality problems are put into place, and existing data errors are corrected, it is often helpful to implement on-going data quality metrics.  Metrics provide visibility to data quality issues so we can react quickly when they arise. Those same metrics can show us where things are working so we can let us turn our attention to other priorities.  There is also an art to metrics – understanding that metrics change behavior and designing them so you promote the behavior you intend.

If data quality is important to your data governance efforts, join us to learn important points to successfully design and implement data quality metrics:

  • Connecting data quality metrics to business needs
  • Metrics etiquette
  • The role of data governance in metrics
  • Visualization considerations
  • Cautions - how to avoid getting what you ask for, but it is not what you want

This session assumes the attendee is already familiar with basic data quality concepts such as data quality dimensions, the information life cycle and how to conduct DQ assessments.

Level of Audience
Advanced

Speaker:
Danette McGilvray Danette McGilvray
President and Principal
Granite Falls

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Wednesday
November 16
1:30–4:45

 

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W3 - Implementing Agile Data Governance  
Tami Flowers,  Director, Governance Solutions,  MetaGovernance Solutions LLC

This workshop provides in-depth real-world examples, templates, how to ’s and lessons learned for implementing data governance in an Agile framework. You’ll leave with knowledge, examples, and artifacts you can use to implement an Agile Data Governance framework.

Agile principles align very well with the keys to success for Data Governance. Using Agile methodology for Data Governance focuses on deliverables that are valuable to the business and continuously introduced into the organization. These are delivered through close collaboration of motivated individuals. Through continuous improvements to the Data Governance process, an organization can remain flexible, compliant, and responsive; and end up with an integrated data governance program that enables the delivery of accurate and timely information for operational or financial disclosure needs.

This workshop provides experiences and examples of Agile Data Governance.

 During this session you will learn:

  • Different approaches to Agile and Lean and how each can be used with Data Governance.
  • What an Agile Data Governance framework looks like.
  • How to align the principles of Agile with the Data Governance framework.
  • In-depth how to’s, real-world examples, and hands on practice for implementing or maturing Data Governance using Agile.
  • Using an Agile framework to be more responsive to Data Governance issues, regulatory changes, audit/exam findings, and the like.
  • Examples of artifacts and templates you can take with you and use. 

Level of Audience:
Intermediate

Speaker:
Tami Flowers Tami Flowers
Director, Governance Solutions
MetaGovernance Solutions LLC

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