Conference Sessions and Afternoon Workshops
November 16, 2016
Wednesday November 16 7:303:30 |
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Wednesday November 16 7:008:00 |
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8:00 - 8:50 CONCURRENT SESSIONS | |||||||||||||||||||||||||||
Wednesday |
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:
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Wednesday |
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:
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Wednesday |
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: |
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8:50 - 9:20 COFFEE BREAK AND EXHIBITS | |||||||||||||||||||||||||||
9:20 - 9:50 DATA GOVERNANCE SOLUTIONS | |||||||||||||||||||||||||||
Wednesday |
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:
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Wednesday |
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: |
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9:50 - 10:10 ROOM CHANGE | |||||||||||||||||||||||||||
10:10 - 11:00 CONCURRENT SESSIONS | |||||||||||||||||||||||||||
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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:
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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.
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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:
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11:00 - 11:15 ROOM CHANGE | |||||||||||||||||||||||||||
11:15 - 12:15 | |||||||||||||||||||||||||||
Wednesday
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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:
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12:15 - 1:30 LUNCH AND EXHIBITS | |||||||||||||||||||||||||||
1:30 - 4:45 AFTERNOON WORKSHOPS | |||||||||||||||||||||||||||
Wednesday |
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:
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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:
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 |
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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:
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