Conference Sessions - June 29, 2011
| Wednesday 29 June 7:30–8:30 |
Registration and Continental Breakfast | |||||||||||||||||||||
| 7:30 - 8:15 | ||||||||||||||||||||||
Wednesday
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Can
Data Really Be Governed? PANEL Moderator: Michael Scofield, Asst. Professor, Loma Linda University Mike Ferguson, Managing Director, Intelligent Business Strategies Ltd Sunil Soares, Director, Information Governance, IBM Software Group Martha Dember, Solution Partner, EMC Consulting Salvatore Passariello, Director, PwC
Join us for an early morning panel discussion where these and other questions regarding the realities of data governance will be discussed. |
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Wednesday
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Meet the MPO and Learn How to Include Governance in Your Metadata Strategy Dan Myers, VP of Operations, Meta-Data Professional Organization The Meta-Data Professional Organization (MPO) is a non-profit international association comprised of business and IT professionals in all areas of meta-data practice. The MPO brings together individuals with interests, expertise, or hands-on experience in meta-data use from all areas of private and public enterprise throughout the world and seeks to disseminate technical and professional information to meta-data practitioners of all levels of experience. Join us on Wednesday morning June 29th and learn more about the MPO and participate in a discussion on governing metadata. Key discussion topics include:
This meeting is open to all conference attendees. You do not need to be a member of the MPO to attend this meeting. For further information about the MPO please visit www.metadataprofessional.org. |
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Wednesday
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Getting Buy-In for
Data Quality through Effective Communications Laura Sebastian-Coleman, IT Manager, Data Quality, OPTUM Insight Cynthia Hartman, Sr. Business Consultant, The Hartford Financial Services Group More often than we would like, people’s eyes glaze over when we start talking about data quality or governance. Another issue is that many refuse to acknowledge that data quality problems exist, because they are afraid to be blamed for them. Effective communication means communication that sticks: people engage in the dialogue, remember your message and act on it. How do we craft effective communications so we can enlist the support of our colleagues? What is the role of metaphors and stories? How do we create a blame-free environment that promotes trust and open discussion of the data quality problems that hurt business performance? Join this engaging and interactive session to hear and share best practices for effective data quality and data governance communications. |
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 8:30
- 9:30 CONCURRENT SESSIONS |
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Wednesday
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SRP's Voyage
Toward Enterprise Information Stewardship: Boldly going where no utility
company has gone before! SRP's Stewardship program develops an Enterprise Information Management Discipline through a sustaining change model; closing the loop between measuring Information Management (IM) behaviors and advancing organizational IM maturity. The following components highlight the program:
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Wednesday
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6 in 60: Six Data Governance Case Studies in Sixty Minutes Robert S. Seiner, President and Publisher, TDAN.com/ KIK Consulting & Educational Services This one hour session from Robert S. Seiner will quickly cover case study samples from six successful data governance program implementations. The pace of this session will be fast and will be arranged to highlight similarities and differences in the approaches that were used by these organizations. Items that will be discussed include:
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Wednesday
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How to Integrate DG into your Enterprise Strategy: Create Visibility, Impact and a Cultural Fit for Your Program ARC will share how they have integrated all aspects of their Data Governance Program into their Strategic Plan, Strategy Maps, Enterprise Risk Map, Divisional/Departmental Balanced Scorecards, cascading the program down into the organization. This process has ensured the viability and cultural fit of data governance down to the lowest levels of the organization. Evolution of the program has provided for improving the capabilities of individuals as well as groups across the company while, at the same time, meeting the evolving needs and delivering value to the organization. |
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Wednesday
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Using Data
Governance to Mature End-User Computing Sean Kimball, Chief Enterprise Architect, MetLife In many enterprises spreadsheets are used in large numbers for financial modeling and various kinds of reporting. However, this widespread use carries with it risks arising from data quality and other issues. Yet, the convenience of spreadsheets is well-liked by users. How do you change this environment? This presentation describes a multi-pronged approach taken in a large bank that encountered such a situation. It is a mixture of both governance and empowerment of end-users, and includes the introduction of a new architecture for data access. Users are able to locate data they require and assemble it in new end user environments where they can create reports in a more controlled fashion. A semantic layer enables the users to perform the data discovery. This approach solves many of the issues that have occurred in spreadsheet-driven environments. Attendees will learn:
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Wednesday
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Data
Visualization: Achieving Quality at the End of the Data-to-Information Life
Cycle Michael Scofield, Assistant Professor, Loma Linda University Data goes through many steps before it becomes information whose ultimate value is realized when supporting major decisions by managers and executives. How that information is finally computed and presented contains significant quality issues. Decision-makers don’t want to worry about granularity of data, or how it is integrated, or how it is aggregated and transformed into information. They also are not interested in the various “qualifications” of information expression (all the stuff which should be placed in footnotes), even though they should understand (as Deming put it) the “weaknesses of the data”. But professional competence demands that we tell them enough to not mis-use the data. Then, we must express it in ways which are not misleading. Data management and DQ professionals are also, technically, “business users” of
data, and thus can also benefit from good data visualization techniques.
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Wednesday
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A Data Quality
Program in the Healthcare Industry As we complete our data warehouse and continue to build complex analytical modeling tools with this data, data quality is becoming a significant priority. Therefore, Prime is beginning a data quality program in order to protect its investment in these analytical tools. In the Fall of 2010, Prime initiated a data quality monitoring project in order to build and establish a data quality baseline, as well as define roles and responsibilities for monitoring and improving data quality. The pharmacy benefit plan data was used as a pilot program that can be leveraged across other subject area domains. This presentation describes how we accomplished the following project objectives:
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| 9:30 - 10:15 BREAK AND EXHIBITS OPEN | ||||||||||||||||||||||
| 10:15 - 11:15 CONCURRENT SESSIONS | ||||||||||||||||||||||
Wednesday
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PANEL: Measuring the Value of Your Data Governance Program Learn how your peers at other organizations are measuring and showing the value of their data governance program. Learn how dashboards, scorecards, maturity models, data quality measurements, reporting and much more are being utilized by practitioners to measure and show the value of their programs. |
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Wednesday
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DG Structure – Convincing Your C-Level What Works and Why Got a great structure on paper but cant’ seem to make it fly or are you simply struggling with where to start? Like so many data governance stakeholders you can find consensus around the importance of structure but getting people, especially the top brass to endorse your model is another story. This session provides a detailed account of the fundamental yet often overlooked concepts of a data governance structure and how it satisfies business leader interests. Most importantly it demonstrates the value behind these concepts and why they position the organization for success. Whether you have already implemented a structure or are starting from scratch this session is for you. Join Jim Orr as he talks to the concepts and best practices for establishing a data governance structure that meets the comprehensive needs of the organization and its business leadership. |
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Wednesday
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Recruiting,
Retaining, and Rewarding IT and Data Governance Professionals David Van De Voort, Partner and Senior Consultant in Information Technology Workforce Strategies, Mercer Governance has rapidly evolved to become one of the most prominent and critical management processes within the IT function, and for linking and aligning the IT function with the business. Governance demands new skill sets and competencies of IT managers and professionals. Governance "black-belts" are in high demand and short supply. Locating skilled IT governance talent and retaining and rewarding key IT Governance contributors are among the greatest "people management" challenges facing the CIO and CHRO. In this session we will present current benchmarks for organization structures, role definition, career paths, and compensation for the Governance function and the Governance professionals who staff it. Participants will receive:
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Wednesday
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2011 DG Best Practice Award Finalist In mid-2010, ConAgra Foods was preparing for the end of a three year journey to bring its Supply Chain functions in line with a common operating platform and with it an ongoing commitment to a common Data Governance Strategy. At that time the ConAgra Foods Data Governance Team began to adjust from a system migration mode into a data maintenance mode as well as begin to optimize their Data Governance processes. This focus on continuous improvement, fed an internal Data Governance Team desire to accelerate their evolution from a Point to Point to a Selective Distribution operating model, establishing the organization as an Enterprise function in more than name only. Concurrently, several large scale projects emerged requiring the support of many IT and business resources, including the ConAgra Foods Data Governance Team. This challenge put the ROI of the desire of the DG team to accelerate their evolution, and the ROI of the emerging projects into conflict. In this presentation learn about the challenges that the ConAgra DG team faced as they expanded Data Governance into new frontiers within the Enterprise. Discover how these efforts challenged the widely-held belief that the other business areas could be easily assimilated into the existing Data Governance operating model. Additionally, learn how conflicts created opportunities for new lessons learned and old lessons (re)learned in the evolution of the ConAgra Foods Data Governance Team. |
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Wednesday
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Information Quality: A Journey that Pays Dividends WEL Networks Ltd (WEL) has adopted a progressive approach to information quality, designed to address organizational changes and opportunities in a fast-moving electrical utilities market. These include:
This case study describes how we:
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Wednesday
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Meeting the
Requirements for ISO 8000 Quality Data We are a data dependent society where every event, every individual, every organization, all locations, goods and services are represented by data. This session addresses the intrinsic characteristics of data that define its quality and why quality data is required but not sufficient for quality information. We also discuss how data quality relates to data portability and why data portability is so important when the expected life span of a software application is measured in months and the expected life span of data is measured in decades. This session presents the practical use of ISO 22745 in expressing data requirements, measuring the quality of data and exchanging quality master data.
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| 11:45
- 12:15 GOVERNANCE AND IQ SOLUTIONS |
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Wednesday
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Automating Communications in the Data Governance Process A critical part of data governance is communication among the team members responsible for maintaining the process. EMC Consulting will demonstrate how the EMC Archer tool can automate the workflow and simplify this process. Learn how to streamline the process of tracking issues throughout the resolution lifecycle, including triggering appropriate communications during the process and monitoring results once solutions are implemented. |
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Wednesday
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Developing an Information Governance Strategy Sunil Soares, Director of Information Governance, IBM Software Group Today more than ever, organizations need to make faster decisions based on the information at hand while dealing with increasing privacy risks and the ever growing requirements to comply with regulations. All of this is driving organizations to recognize the need to take a more strategic approach to managing information. For these reasons, information governance is an increasingly important area that is directly tied to an organization’s ability to enhance the quality, protect, audit, manage and ultimately increase the value of your organization’s enterprise information throughout its lifecycle — into Trusted Information. Join Sunil Soares, Director of Information Governance at IBM, as he discusses the core information governance disciplines that can help enhance your organization’s capabilities by leveraging people, process and technology to ensure your enterprise information is of highest quality, protected and managed throughout its life-cycle. | |||||||||||||||||||||
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Wednesday
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Leveraging Data Governance Maturity Models Salvatore Passariello, Director, PwC Data Governance Maturity Models help organizations understand their current level of information management maturity. Used correctly it can be instrumental in assisting organizations in identifying an appropriate data governance framework and roadmap for future data management growth. When an organization embarks on the Data Governance journey it is first important to understand and identify your current stage of maturity and where you aspire to be in the future (1 year, 2years, and 3 years out). Organizations that plan this evolution in an organized and structured way will gain competitive advantage over those organizations that are forced to change due to external and regulatory forces. The Data Governance Maturity Model can help provide the structured approach required to develop your Data governance framework, strategy and roadmap to data excellence. During this session we will discuss PwC's approach to leveraging and adapting Data Governance Maturity Models to fit your organizational culture. Additionally we will walk thru a case study focusing on how Data Governance Maturity models were leveraged to develop an organizations CDI Governance framework, strategy and Roadmap. | |||||||||||||||||||||
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Wednesday
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How Metadata Management Will Help you Avoid Lawsuits and Keep Your Job When Audited James Cerrato, Chief Product Evangelist, Adaptive Jeff Goins, CEO, Adaptive Are you ready when auditors ask questions like these?
This presentation will show how the Adaptive repository solution provides the capabilities critical to achieving successful data governance and compliance.
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| 1:30 - 2:30 CONCURRENT SESSIONS | ||||||||||||||||||||||
Wednesday
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Data Governance
for Business Decision Management Systems Jacob Feldman, CTO, Open Rules Whether it is loan approval, insurance underwriting, customer service tactics, or something else, business decision can affect customer satisfaction, competitive analysis, and profitability. It puts Business Decision Management System (BDMS) in the center of modern enterprise architectures. A good BDMS needs to support a full cycle of discovering, maintaining, testing, and executing decision models, including governance of decision support data. While decision models and supporting business rules usually maintain highly efficient data connections, they should remain completely independent from the data organization and data sources. However, there are two types of decision support data that are subject to a special governance concern: a) test data that covers all possible combinations of fact types for inter-related rule families; b) historical data that serves as a source for business rules discovery, their compression, and "ever-going" learning. In this presentation we share real-world experience with planning, implementation and control processes to provide and maintain such data. We will present concrete examples of decision models and related data governance processes. |
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Wednesday
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Maturing Data Management Governance at UPS UPS is the world's largest package delivery company and a leading global provider of specialized transportation and logistics services. In 2010, their Data Management Department was asked to go build Data Governance. The team assigned to the task quickly found that the foundational capabilities that were necessary for Data Governance lied within their own domain of responsibility. Before an effective Data Governance program could be rolled-out to the Enterprise, the Data Management Department would have to fortify their own governance controls. Over the following year, with a tight budget, they developed and implemented various governance processes and capabilities including:
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Wednesday
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Choosing Your Data Governance Strategies: From
All-You-Can-Eat Buffet to Haute Cuisine Pablo Riboldi, Information Governance Manager, LDS Church It seems that DG strategies are as numerous and varied as the plates served at a cruise’s 24-hour buffet. However, the strategies for a particular DG program are probably more like the menu at fast-food corner stand. Nothing wrong with that, because you need to focus your resources on the most valuable strategies for your organization, choosing the best strategies for your DG Program is critical. But, how do you choose? What do you choose?
This session will help you present the strategies for your own DG Program as a finely crafted menu for best taste of your organization. |
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Wednesday
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Data Governance of
Unstructured Data and Documents - Case Study of a Health Insurance Company April Reeve, Senior Practice Consultant, EMC Consulting The majority of data in any organization is unstructured (found outside relational databases). Additionally, some businesses have a specific focus on document management and unstructured data such as mortgage companies, pharmaceutical firms, and health insurance companies. Health insurance companies have a lot of physical and electronic documents to manage particularly because of the claims that are submitted and the accompanying material. The Data Governance program at this health insurance company was initiated out of the Legal department as well as the IT organization. Recently, there is a special emphasis in Data Governance, especially around document management, around creating and acting on data retention policies and expiration dates. Organizations are looking for an opportunity to lower the volumes of stored data by eliminating any data that does not need to be kept. Legal departments are emphasizing the risk around keeping any data (including and especially email) that is not specifically required.
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Wednesday
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A Guide to Improving Data Quality by Eliminating Duplicate Data Using
Entity Resolution John Talburt, Professor, Information Science at the University of Arkansas at Little Rock Yinle Zhou, Research Associate, Information Science at the University of Arkansas at Little Rock Many data quality problems are the result of duplicate and redundant master data within and across operational systems. Unlike data cleaning and standardization tools that address problems at the record level, the elimination of master data duplicates requires methods and techniques that successively compare, group, and purge large numbers of master records. This session will explain four basic approaches for solving this problem including record linking, database join, identity resolution, and identity captures. It will also cover three case studies highlighting the use of these approaches. Topics include:
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Wednesday
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Driving Information Quality Management Through ISO 9001 - A Case Study Grant Robinson, Information Quality Coordinator, NSW Office of Water Our organization has employed the ISO 9001 Quality Management System since 2001 to underpin its operations, monitor its practices and drive continuous improvement. This case study describes the fundamentals of ISO 9001 and shows how we have implemented the standard to drive information quality. Topics include:
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| 2:45
- 3:45 CONCURRENT SESSIONS |
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Wednesday
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Implementing Data Governance through Project Methodology David Plotkin, Manager of Data Governance, AAA of Northern Ca, Nevada, and Utah When it comes to Data Governance, it seems like a good idea to integrate the whole process – including metadata and data quality – into any project that handles data. To do so, you need to add milestones, tasks, artifacts (such as forms that need to be filled out) to the project plan, ensuring that all these items find their home in the correct stage of the project. But what do these items look like, and where is the proper place to put them in the project methodology. And how do you establish responsibility and staff a project with the necessary skill set to make sure everything gets delivered. This presentation answers these questions, discusses the logistics of maintaining the Data Governance artifacts, and provides detailed examples of the forms needed. You will learn:
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Wednesday
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Data Governance Communications Peter Aiken, Founder, Data Blueprint This talk will describe steps required to develop data governance communication. While data governance isn't a new concern for organizations, many parties are newly exposed to the wider needs for data governance and the unacceptable results of poor data governance increasing awareness. Developing an efficient/effective communication plan is a critical success factor in the success of any data governance organization. In the past, the majority of plan focus has been on technical aspects of data governance. Now we know that at least three data governance communication-types (internal, responsive, and proactive) are required for your organization. Other aspects of data governance communication planning include: when specifics are required, where to get certain information, and how to develop and implement the plan. |
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Wednesday
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Structuring Data Governance: Automation, Communication and Policy Management When Scotiabank México decided to focus on using data governance to drive higher integrity, in particular, consistency of their data, they knew they wanted to base their program around managing and improving the data policies that help drive their business processes. The challenge was how to efficiently operationalize those data policies to offer tangible value to business users. This presentation will discuss the prescriptive approach Scotiabank Mexico took to data governance and the processes they are implementing to manage, communicate, implement and enforce those policies. Specifically, this presentation will cover how Scotiabank was able to:
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Wednesday
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Business Cases for
Data Quality and Straight-Through Processing Nancy Pullen, Data Quality Manager, EnerNOC Inc Question: How do you manually clean up and process over 50 million records/day? Answer: You can’t! Enter data quality and straight-through processing. As a start-up company with 20 people and few customers, we were able to visually inspect our incoming data and manually fix data points in critical event windows when necessary. As a 500-person company with over 7,000 customers, 50 million records/day, and a need for 24/7 data quality, this is not only infeasible, it’s bad business! This case study describes the business cases we developed to address the needs of the organization’s decision makers in key departments, in order to secure their support for data quality and straight-through processing |
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Wednesday
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Data Quality In Display Advertising Mariena Quintanilla, Data Quality Lead, Yahoo! Jaya Pati, Sr. Quality Engineer, Yahoo! After establishing a successful Data Quality program in one part of the company, the Yahoo central DQ team was asked to expand to cover all company data systems. Having come from a different "side" of the company the DQ team was confronted with multiple challenges in the new divisions:
The approach used has been refined over the past year to meet new divisional challenges with a continued focus on the major DQ program success factors: core monitoring system, strong product stakeholder and data customer engagement, lean/scrappy delivery of incremental solutions. This has been challenging but has helped us get to an execution structure that is already delivering results and improving the quality of data in the new systems. In this presentation we will share challenges and solutions combining a "top down" and "bottom up" execution model in implementing DQ in different business models and data systems. |
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| 4:00 - 5:00 KEYNOTE PANEL | ||||||||||||||||||||||
Wednesday
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KEYNOTE
PANEL: As Data Governance and Information Quality mature, the two disciplines face many traditional challenges while they evolve to adapt to new business imperatives. As we reflect on the past three days, what questions are beginning to emerge about the coming years? What do the future of Data Governance and Information Quality hold? Join this exciting panel to discuss the following and more:
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Wednesday
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Data Governance Professional Organization Interested in learning how your colleagues are addressing data governance at their organizations? Join us after the keynote panel and network and share your experiences.about these groups and how they will help you in your data governance programs. |
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Wednesday
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International Association for Information and Data Quality (IAIDQ) Meeting All are invited to attend this meeting to get the latest update on IAIDQ activities including the IQ certification. You will also meet IAIDQ members and others who are interested in the association, and network with others who share a keen interest in information quality. IAIDQ leaders will present a brief overview of 2011 goals and solicit your input and ideas for future plans. Add your voice to the conversation!! |
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