Pre-Conference Tutorials and Conference Sessions -
June 3, 2019
| Monday June 3 7:30–8:30 |
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| 8:30 - 11:45 MORNING TUTORIALS | |||||
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T1: The First 11 Steps to Starting a World-Class Enterprise Data
Governance Program David Marco, President, EWSolutions This tutorial presentation will instruct attendees on the first 11 tasks that your data governance program will need to accomplish. Organizations that properly complete these steps are well on their way to a successful data governance program. Participants will leave the workshop with a collection of artifacts that can provide real world success. Usable, detailed templates and processes will be provided and examined, based on the real-world experiences in data governance and data quality with major organizations. Attendees will be able to customize these artifacts to suit their organization's needs and culture. Learning Objectives will include:
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Monday
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T2: A
Roadmap for Building a Successful Data Quality Program: How to Get Started, and
How to Assess and Improve What You Have John Talburt, Professor, University of Arkansas at Little Rock Accurate business reporting and data analytics can only be achieved using high-quality data. Yet many organizations either do not have a data quality program, or they just focus on standardizing source data. Having a complete, ongoing program to measure, monitor, and improve the quality of data is a competitive advantage for an organization in today’s data driven economy. This tutorial is primarily for participants starting a comprehensive data quality program or wanting to assess and improve the capabilities of an existing data quality program. Participants will learn:
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Monday
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T3: Assessing Your Existing Data Governance Program Robert S. Seiner, President/Publisher, KIK Consulting/TDAN.com Your Data Governance is now a couple of years old. You engage your Data Stewards. You make good use of your Data Governance Council. And you demonstrate consistent value to your organization. Or do you? Is this the state of your Data Governance program? Have you climbed every mountain? Do you feel like you are running out of places to add value? Perhaps there are there aspects of the program that can be improved. This tutorial with Bob Seiner will focus on how to assess your existing data governance program, articulate strengths and address specific opportunities to improve. Bob will share advanced data governance techniques used to expand the focus from the disciplines you already formally govern into disciplines such as information quality, data protection, metadata or master data management, or even the lauded Big Data discipline. The session will help you move from routine to progressive. In this session you will learn:
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Monday
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T4: Growing
Your Data Governance Program: Progress vs. Meaningful Impact Kelle O’Neal, Founder and CEO, First San Francisco Partners “What gets measured gets done.” Or does it? One of the biggest challenges in standing up and sustaining a data governance program is determining the true impact the program has made to the organization. When it comes to quantifying data governance success, metrics can help you establish a baseline, track your progress against goals, align expectations and even defend change – or additional funding. But while metrics are a good start, as they are necessary to ensure alignment, relevance and value of your data governance initiative, they are not enough to truly translate data value into business value. You MUST link progress metrics with impact metrics and align everything to key business goals. In this tutorial, Kelle will provide tips and best practices for:
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Monday
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T5: Designing Modern Data Governance for the Data-Driven Business Donna Burbank, Managing Director, Global Data Strategy, Ltd Becoming a data-driven organization is a key focus for the future innovation plans of organizations across many industries and regions. The drive for fast-paced innovation and emerging technologies trends like IoT, Big Data, advanced analytics, and more can seem at odds with data governance. But modern data governance approaches can augment business value with faster time to market built upon a strong data foundation. This workshop provides practical approaches based on experience from real-world implementations to help you define a modern data governance program to support your organization’s business initiatives. Topics include:
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Monday
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T6: Successful
Data Governance for Data Lakes Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners Data Lakes are becoming increasingly common in enterprises, and they present a new level of challenges for Data Governance. Data Governance is essential for the success of a Data Lake but must overcome a number of challenges. For instance, many enterprises have to acquire a wide diversity of data that must be cataloged within the Data Lake and must protect private and confidential data. This tutorial describes the tasks that a Data Governance function must perform for a Data Lake, and the capabilities that Data Governance must develop to the requisite level of maturity. Particular attention is paid to Data Acquisition, Data Preparation (“Wrangling”) and the needs of analytical models. Technologies, such as the Data Catalog, that support these activities are reviewed. The relationships that Data Governance must establish with a wide range of units are described including relationships with Legal, Procurement, Risk, Compliance, Privacy, IT Security, Data Scientists, Data Architecture, and more. Overall, Data Lakes are driving Data Governance to play a coordinating and harmonizing role, which can be considered as a new way of working for Data Governance. Attendees will learn:
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| 12:00
- 12:30 SPONSORED SESSIONS - DATA GOVERNANCE AND DATA QUALITY SOLUTIONS |
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Monday
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| 1:30 - 4:45 AFTERNOON TUTORIALS | |||||
Monday
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T7: Practical Steps for Overcoming Political
Challenges in Data Governance David Marco, President, EWSolutions Data and information are critical assets of any organization, and should be considered as valuable a resource as buildings, employees and products. As a result, the study and implementation of Data Governance programs have become key initiatives for most large organizations. For a company to be successful in this endeavor they must first defeat the greatest obstacle of any data governance program…POLITICS!! This intensive session will teach you about the 6 types of “problem” people that Data Governance programs traditionally have to deal with:
Most importantly the attendee will learn the 7 best practices for dealing with these problem people. These best practices will be presented in great detail with real-world examples provided for each of the best practices. Level of Audience |
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Monday
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T8: Digging Deeper into Data Quality Management: Standards,
Metrics, and Controls John Talburt, Professor, University of Arkansas at Little Rock There is always room for improvement and data quality management programs are no exception. This seminar is aimed at participants already engaged in data quality and would like to learn more about some of the more advanced techniques for assessing, monitoring, and improving data quality. The tutorial will cover:
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Monday
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T9: Managing the Changes - How to Make your Data Governance Program Sustainable John Ladley, Principal, Sonrai Solutions Data governance equals change, and managing change is the number one obstacle to Data Governance success. Managing change is required for a sustainable program, so the changes associated with data governance need to be identified, and the organization needs to be carefully led from current state to future state. Too many data governance and information management programs end up as “shelf-ware”. This is expensive and disheartening. Simply put, Data Governance will not succeed without managing the changes and leveraging your culture. It seems it is more difficult than it should be. Any group working to make data governance sustainable needs to understand why this is hard, ad what needs to be done. This tutorial is specifically aimed at sustaining EIM programs, especially data governance. This includes an organization change management effort unique to data governance, data quality and other programs. This class will cover in detail the barriers to overcome and sustain the many efforts and initiatives required for successful EIM. Attendees will leave with a basic tool kit for organization change management for DG. This tutorial will cover:
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Monday
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T10: Catalogs, Glossaries and Dictionaries - Governing the
Metadata Robert S. Seiner, President/Publisher, KIK Consulting/TDAN.com Organizations are implementing glossaries, dictionaries and data catalogs for numerous reasons. The delivery of these forms of data asset documentation requires governance of the information collected therein. The governance must be focused on the definition, production and use of this metadata. Join Bob Seiner to understand the actions necessary to build and sustain successful glossaries, dictionaries and catalogs that improve the understanding of data, quality of data and protection of sensitive data. Bob will share best practices that lead to value received by these organizations. In this tutorial, Bob will discuss:
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Monday
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T11: A Review of Data Governance Tools Sunil Soares, Founder & Managing Partner, Information Asset This tutorial will cover data governance tools for the following requirements:
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Monday
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T12: Implementing Agile Data Governance Tami Flowers, Director, Governance Solutions, MetaGovernance Solutions, LLC Once Data Governance has become a priority for your organization, how can you make it operational within existing Agile projects? Bringing together data, information, reporting, reconciliations, controls and stewardship into a platform to provide "one version of the truth" for an organization is not a small, or quick task. In this session we will discuss the key components of establishing a Data Governance Framework and expand into how to make it operational within Agile projects. Using Agile methodology for Data Governance focuses on deliverables that are valuable to the business and enable an organization to continuously build out an integrated data governance program that delivers accurate and timely information for operational or financial disclosure needs. This will be an interactive session and we will use real examples so you can leave with ideas and knowledge that you can immediately use. We will cover:
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| 5:00
- 5:45 Conference Sessions |
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Monday
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Industry Special Interest Group - N0N-PROFIT Improving our Data Driven Culture to Strengthen the Lives of Children and Families Autumn McCants, Data Governance Manager, Starfish Family Services David A. Williams, Chief Administrative Officer, Starfish Family Services Starfish Family Services is a private, nonprofit human service organization, recognized as a champion for under-served children and families in metropolitan Detroit. With over 500 employees, we provide high-quality programs and support services across 19 sites, with a focus on early childhood development mental wellness and empowering families. Starfish also has a reputation for operational excellence, with a focus on measuring outcomes in a data driven and evaluative culture. This presentation is a case study on how Starfish is implementing a large-scale data governance program and the skills needed to manage change and shift culture. This presentation will cover:
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Monday
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Industry Special Interest Group - HEALTH CARE Expanding Data Governance from a Data Warehouse Function to an Advocate of Core Values Across an Enterprise Yolanda Griffin, Sr. Data Governance Analyst, Blue Cross and Blue Shield of Louisiana Brian Badinger, Director, Enterprise Data Management, Blue Cross and Blue Shield of Louisiana The mission of Blue Cross and Blue Shield of Louisiana (BCBSLA) is to improve the lives of Louisianans by providing health guidance and affordable access to quality care. The inception of Data Governance at BCBSLA was initiated as a result of the Enterprise Data Warehouse implementation. As the company goals matured to incorporate new strategies, the Data Governance Office was commissioned to expand its scope in assisting with delivery of the core foundational capabilities necessary to achieve BCBSLA’s mission. Our focus on Data Stewardship, Data Management, and Partnerships allowed us to manage the integrity and security of enterprise data. As a result, this enabled predicative analytics which supported provider care and preventative care management initiatives. Session highlights include transformation activities and life-cycle phases for maturity: Topics include:
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Monday
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Industry Special Interest Group - PUBLIC SECTOR Implementing Data Stewardship at the Bureau of Safety and Environmental Enforcement Julie Conklin, Sr. Data Management Analyst, Bureau of Safety and Environmental Enforcement The Bureau of Safety and Environmental Enforcement (BSEE) is spending over $20 million dollars a year collecting and storing information. This data is compiled in many different ways and with varying standards. Some of this data is used once for reporting and stored in multiple databases which make it difficult to share or to aggregate in order to understand regional or national conditions or trends. The Bureau's first Data Stewards are working to improve how data is collected, stored, and used so it can meet its responsibilities to inventory and report on the condition of public land. With the support of the Director and Department, BSEE implemented its first Data Stewardship Strategic Plan, Data Stewardship Team, and Data Stewardship Council. So far, the team has been working to:
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Industry Special Interest Group - FINANCIAL SERVICES How is Data Risk Planned for and Operationalized Across a Data Governance Program Stephanie Grimes, Sr. Tech Lead, Freddie Mac Zainab Asif, Risk and Controls Manager, Freddie Mac As data governance programs are established, a foundational aspect that needs to be considered and strengthened is data risk management and its implications. In this session, we will provide an overview of how a data risk strategy was implemented to address the inherent risk of doing business within a financial institution. What you will learn:
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Monday
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Industry Special Interest Group - INSURANCE Data Quality Through Business Model Templates Venkata Komaragiri, Technology Manager, State Farm Kevin Knipmeyer, Technology Manager, State Farm This presentation will discuss the success of improved data quality through capturing the variations of chronological business scenarios on relational data. We will describe how we took an existing problem of unknown coverage for complex business processes to create test data and identified a designed solution to automate both test data and data quality checks for data transformation. We will show how it impacted our ability to deliver quality products, to provide complex transforms and move data to a new platform on an ongoing basis, with a much higher degree of confidence at a lower cost. Level of Audience |
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Industry Special Interest Group - RETAIL Transforming Siloed Teams into a Collaborative Powerhouse Aida Biberic, Data Governance Analyst, Columbia Sportswear Company Jennifer Canney, Enterprise Data Architect, Columbia Sportswear Company When teams don’t share what they’re working on, groups with similar goals can end up misrepresented, communicating the same message with the same partners, or conveying a slightly different message that is ultimately trying to say the same thing. We have worked diligently over the past two years to ensure that our Data Governance, Information Security, and Enterprise Architecture teams are in sync, proliferating a united message, and working together to accomplish our goals. Our relationships started out of necessity and have since matured into a functioning, proactive, collaborative powerhouse. We want to share our big “How’s”: how we started, how we’ve grown, how we share, and how we raise awareness for one another. Topics include:
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