Conference Sessions - June 9, 2010
| Wednesday 9 June 7:30–8:30 |
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| 7:30 - 8:15 SPECIAL INTEREST GROUPS | ||||||||||||||||||||
Wednesday |
How Insurance Companies Are Addressing Data
Governance Jim Viveralli, Erie Insurance Group The Insurance Special Interest Group will focus on data governance in the insurance industry. There will be a short presentation on some of the activities going on with the Insurance Data Management Association (IDMA). You do not need to be an IDMA member to attend. This session will also include an open forum discussion regarding last years Insurance SIG discussions and any improvements in data governance implementations since then. Although, this session is meant to foster collaboration on best practices and shared experiences in implementing data governance in the insurance industry it is not limited to insurance carriers. Consultants and vendors with experience in the insurance industry are also welcome to attend. |
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Wednesday |
Developing Effective Data Quality Metrics Laura Sebastian-Coleman, Ingenix/UnitedHealth and IAIDQ Everyone needs great IQ metrics, but few know how to develop them. Join this highly interactive session to share and learn best practices! You will leave with practical tips you'll be able to implement right away. |
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Wednesday |
Data
Standards and Regulations - The
Challenges of Data Governance in the Financial Sector Greg Zegarowski, Financial Leadership Corporation Meeting regulatory requirements and extracting value from rich databases are critical objectives for financial services companies. What are the emerging regulatory challenges in customer privacy and data security? What are some new developments in technology standards that will affect how data governance is conducted and how data will be collected and shared by regulators and industry participants? Topics include:
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 8:30
- 9:30 CONCURRENT SESSIONS |
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Wednesday
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Rolling Out a Data Governance Program in a Perfect
Storm: Bottom-Up Meets Top-Down At Harvard Pilgrim Health Care, data governance began as almost an ad hoc effort as groups of concerned stakeholders, cajoled and facilitated by IT, coalesced around particular data pain points. When the organization embarked on its five-year IT strategy to replace its core administrative system and promote the adoption of an Enterprise Data Warehouse, executive attention was suddenly focused on our core data management capabilities and gradually maturing data governance program. This newfound set of strategic imperatives changed the conversation, turning skeptics into advocates, shifting the leadership to business rather than IT, and supplying the rationale for completing the data stewardship journey undertaken years before. This session will provide a case study of one organization’s efforts to implement a data governance framework and associated data stewardship responsibilities that responded best to its particular challenges. Discussion will focus on its organizational context, the governance model adopted in response to its particular business drivers and corporate culture, and activities undertaken to mature its capabilities in a progressive yet non-intrusive manner. Ongoing challenges, lessons learned along the way and future opportunities for governance program enhancements will also be described. |
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Wednesday
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Show Me the Money Nancy Curtis, The Wise Enterprise Open your mind to the power of data governance principles and practices. Success stories from a practitioner show the unlimited potential to deliver business results that will gain you broad executive support and a prominent place in the organization. Think like the executives in Finance, Marketing, Sales and Operations, and you will become a powerful partner who doesn't just solve data problems, but provides a platform for strategic advantage.
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Wednesday
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How to
Deliver a Data Governance Communication Plan Robert S. Seiner, KIK Consulting & TDAN.com This hour session focuses on two distinct areas where effective communications planning can quickly and inexpensively support all aspects of a data governance program. These two areas are 1) data handling / communications and 2) data awareness / security. This sessione introduces a simple tool that can be used to dramatically improve the planning around data communications, and improve awareness around data security and risk management concerns. The session will focus on laying out a plan that addresses:
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Wednesday
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Life
Before and After Creating a Data Governance Team Rich Murnane, iJET International Falguni Sanghani, iJET International iJET International is a global provider of business resiliency that allows corporate risk managers to protect employees and other assets around the world and gain greater control around the operating risks. Rich Murnane and Falguni Sanghani from iJET will share historical details of life before and after iJET’s decision to create a Data Governance team. The presentation will provide insight on the following topics:
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Wednesday
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Measurement in the
Middle: A Data Quality Assessment Framework Laura Sebastian-Coleman, Ingenix/UnitedHealth and IAIDQ Most often people talk about data quality measures at either a very abstract level (dimensions of data quality) or an extremely specific level ("I need to measure this problem..."). To avoid these traps, a team at Ingenix developed the Data Quality Assessment Framework (DQAF). Focusing on four objective data quality dimensions – completeness, timeliness, validity, and consistency – the DQAF defines 37 measurement types that can be applied to relational data (e.g., consistency across multiple columns). This paper discusses how the DQAF enables establishment of core measures and consistent implementation of data quality measurement and assessment through standardized processes and a common model. Participants will learn about:
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Wednesday
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Strategic Partnerships in Data Quality and Data
Governance Kira Chuchom, Cisco This presentation covers Cisco’s experience and evolution in Data Quality and Data Governance, from leveraging a federated Data Governance framework, deploying a Data Quality Improvement methodology that includes a Data Certification process, building a Data Quality Center of Excellence that is co-led by key business and IT stakeholders, sustaining a thriving Stewardship Community, to usage of data quality tools. Also included is a real-world guide in relationship building, engagement management and executive sponsorship in the cause of Data Governance. Key success differentiators:
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| 9:45 - 10:45 CONCURRENT SESSIONS | ||||||||||||||||||||
Wednesday
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Global Data Management: A Practitioner’s Perspective Jiro Sakamoto, Global Data Excellence This case study will involve the progression of data governance based on a large CPG company during their business transformation of consolidating all their disparate market systems into a global entity. Jiro will review the organizational structure adjustments as more organizations implement a global data management strategy. He will explain the importance of the roles and responsibilities in leading this transformation. We will share the success stories as well as the learning from mistakes as data performance indicators are put in place. |
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Wednesday
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Classifying Sensitive Data: Governance Tips & Traps Parallels between complex information infrastructures and radioactive bar stools David Schlesinger, Metadata Security LLC The FBI found that 61% of all inappropriate corporate data exposures are the result of employee ignorance. This is the same type of knowledge-loss that created a dangerous public health hazard in 1984 when employees of a hospital sold old nuclear medicine equipment for scrap. Corporate ignorance of data sensitivity allows employees to download entire private databases onto their laptops, which are subsequently lost or stolen. The talk will discuss chief causes of corporate knowledge loss, and outlines a workable strategy for capturing information sensitivity within the infrastructure itself. This method will provide a way for all knowledge-workers to know which information can be shared and which information must be tightly protected. David will also explain how informed planning can support data regulatory compliance within business processes while also increasing corporate agility. |
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Wednesday
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Data Governance for CXOs Steven Adler, IBM The IBM Data Governance Council predicted that Data governance will become a regulatory requirement in an increasing number of countries and organizations. In some countries, organizations will have to demonstrate data governance practices to regulators as part of regular audits. They also predicted that The value of data will be treated as an asset on the balance sheet and calculating risk will be used more pervasively across enterprises for small and large decision-making and will be increasingly automated by information technology. The Chief Financial Officer will be tasked with reporting the quality of enterprise data and amount of capitalized risk and these metrics will become key performance indicators and market benchmarks. This presentation will explore these new requirements and offer best practices and solutions for CXOs. |
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Wednesday
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How to Get Buy-In for
Data Governance John Ladley, IMCue Solutions Jim Viveralli, Erie insurance Group Organizations need to develop a business case for Data Governance, even if they are not required to do so. How can you measure data governance if you have not set any targets in advance? This presentation will cover the significant drivers for data governance (DG) that offer solid financial results and will expedite solidifying your DG effort. We will review real examples from a successful Data Governance implementation at Erie Insurance Group which will reinforce the objectives of this session. This session will cover:
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Wednesday
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Data Quality in Mergers and Acquisitions Mergers and acquisitions will fail if the data is ignored. To realize the synergies of the merger or acquisition, the data management team must overcome the complex data quality and integration challenges required to ensure all critical processes can execute successfully to support all business imperatives. This presentation highlights the different data quality considerations for the acquisition of a new business. It describes a data quality strategy, framework, methodology, and platform to:
The presentation draws on a real-life scenario including multiple data migration and consolidation programs within a global organization. |
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Wednesday
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Medical Information Quality Through Root-Cause Process Improvement This case study describes how the quality of medical information generated and used by two collaborating groups is perceived differently and what can be done to overcome the resulting data quality problems. The main quality issues were lack of accuracy, incompleteness and poor timeliness. The solution was to apply Total Quality Management (TQM) to identify and remove the root of the problems. We then created a data quality policy which engages both parties. Encouraging results were obtained. However, efforts must be constant especially to unify the views of both groups on the importance of data quality. We discuss how we negotiated data customer-supplier agreements, how we resolved conflicts, and how we overcame the politics that often surround data quality. This presentation also gives an overview of the current challenges in the quality of medical information:
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| 11:00
- 11:30 GOVERNANCE AND IQ SOLUTIONS |
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Wednesday
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The Business Impact of Data Stewardship Data stewardship has never been more critical. Data governance directly affects operating costs, risk management, and revenue. Workflow-driven, centralized data policy management that operationalizes data governance is critical to deriving sustainable, measurable benefits from data governance programs. This session will step through the processes of data policy creation, management, implementation, and measurement from the point of view of the data governance council member and review the “process of data management” from a data steward’s viewpoint, highlighting the benefits that enabling technology can provide. |
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Wednesday
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The Importance of Data Models in Data Governance A large part of any data governance initiative is the understanding and accountability of the core data assets which drive the business. A data model is critical to this understanding and helps align business requirements and definitions with technical implementations. This session will discuss ways in which data models can facilitate data governance, including:
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Wednesday
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Closed-loop Data Governance: Collaborate, Define, Manage & Validate Stijn Christiaens, Collibra As an emerging category, Data governance is often defined as the combination of processes, roles and responsibilities for assuring the correct management of data. From Business to IT architecture and IT operations, creating a closed loop from the business definition of data to the runtime environment of data and back. As such, data governance has some essential ingredients:
We will show how Collibra's Business Semantics Management platform provides you with the capabilities to efficiently execute data governance: the Business Semantics Glossary lets you collaboratively define and govern the meaning of your business assets in their business context and automatically generate new technical models (e.g., XML, UML,XSD,SQL…). The Business Semantics Studio ties meaningful business context to your technical models and (legacy) data sources using context-aware, semantic mappings. The Business Semantics Enabler automatically generates data transformation and data validation services (e.g., REST, WSDL) on top of your existing infrastructure. |
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Wednesday
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Data Governance in Financial Services Greg Zegarowski, Financial Leadership Corporation Customer data is one of the most valuable assets of financial institutions. How that data is mined and protected is critical to success and the use of the data must adhere to regulatory requirements and privacy standards. Going the extra mile and incorporating reputational risk considerations into a data governance program is the hallmark of leading institutions. In this session, you will learn:
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Wednesday
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Setting the Standards:
Deploying Global Governance Arona Primalani, Earley & Associates How do you manage taxonomy and metadata implementation across 20-plus business units, five geographies, and 20 projects? What are the factors that need to be considered when deploying standards that affect taxonomy application and operationalization? Learn how these and other challenges were addressed in a global governance deployment for a large, diverse publishing organization. This is a detailed session covering both strategy and tactical deployment issues. Topics include:
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Wednesday
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Practical Principles Learned in 3 Years of Data
Governance Pablo Riboldi, LDS Church This is a real case study (no sales pitch, no sugar-coating, no aspirin, no buffering agents) sharing the adventures of a 3-year veteran Information Governance Manager at a large non-profit organization. You will learn principles of Data Governance with real life advice on how to apply them and how to avoid common pitfalls. Some of the chapters in this saga include:
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Wednesday
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Data Governance at Groupe
Mutuel Assurances Walid El Abed, Global Data Excellence Limited Eric Michellod, Groupe Mutuel Assurances This presentation will discuss a case study of the startup of a data governance implementation in an insurance company. Groupe Mutuel Assurances (GMA) introduced a new legacy program that revealed data quality issues that needed to be resolved. The Governance Data Excellence framework was introduced and returned control of the decision to business people to perform their job first time right and to help data management people to priorize and correct what matters for the company. We will discuss:
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Wednesday
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IQ Policies and Strategies for Empowering the Knowledge
Worker Elizabeth Pierce, University of Arkansas at Little Rock Our data quality monitoring process has improved business customers’ trust in the ODS and provided a solid foundation for the enterprise data warehouse. Many Information Quality Policies and Strategies have been formulated from an enterprise-wide perspective. In addition to the enterprise, one can also approach IQ Policies and Strategies from multiple levels so as to provide the necessary guidance to deliver a better "information experience" at the business process/functional level, project/application level, and the employee level. This presentation discusses the role of IQ Policies and Strategies at the employee level, helping them to utilize information more efficiently to achieve objectives. This talk identifies five critical areas:
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Wednesday
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Overcoming the Information Quality Challenges of Global
Data Management Kathy Hunter, Kynetika Ltd In recent years, multi-national companies have found that maintaining multiple databases in local offices across the globe does little to provide the intelligence modern companies need to provide products and services that will transcend borders. They realize that a global database can provide richer insight, lower costs and the ability to transfer expertise by promoting centralize best practices but few have been successful. There are very good reasons for this. Around the world there are more than 200 countries, 130+ different address formats, perhaps ten thousand languages, varying naming conventions and a multitude of different cultural influences that must be considered when managing global data and their quality. This presentation will provide some tried and tested methods that can help overcome these challenges. Here's what we'll discuss:
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| 1:45
- 2:45 CONCURRENT SESSIONS |
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Data Management and Governance in the British Army's Personnel Organization: Exploding the Myths Brigadier Richard Nugee MBE, Director of Manning for the British Army, describes how the introduction of data governance, together with a comprehensive program of data quality management, has generated benefits of $20m and opened up the opportunity for greatly improved manpower planning and personnel administration. The presentation will cover:
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Wednesday
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Data Ethics - A Perspective for
Data Governance Anne Marie Smith, 21st Century Insurance For too long data and information management specialists have washed their hands of responsibility for the ways data is used by business people. Generally, a data manager’s professional responsibility for data has been limited to making data and information ‘fit for use’ for a particular business purpose. But what are those purposes, and are they ethical? Is it possible for business to be aware continually of the potential technical or process breaches of ethics in their planned data use? Are business data and information consumers solely responsible for ethical breaches, or is there an advisory role for data and information management professionals (including stewards) in the ethical use of data? This presentation will provide categories and example scenarios where data professionals have an ethical responsibility to influence the proper use of data, and will offer some suggestions for instituting an ethical approach to data management and usage for organizations, by data stewards and officers of data governance initiatives. In this presentation you will learn:
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Wednesday
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Governance in a Transparent Data Environment Pat Garvey, EPA Often data is complicated and numbing to use by secondary users. The legal records is often of poor data quality, thus use is limited. Good Quality assurance procedures, data stewardship and data management practices can improve the legal record and help make the data useful to decision makers and public users. Transparency of actions must be documented and founded on standards. Sunshine to the data is very helpful. Together these actions can transform poor quality data into useful information to a vast user community. EPA has successfully employed these methods to assist in public access, community right to know and various regulatory tools available to staff and the public. The legal record should not be a hindrance to having the data be useful and used in many appropriate ways. |
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Wednesday
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Toro
Surveys the Enterprise Landscape with Data Governance David Gaines, Toro Gavin Day, DataFlux In this presentation, Tony Fisher and David Gaines will discuss the factors that necessitated the creation of Toro’s enterprise data governance program, the current state of the data governance implementation, and how Toro sees its data governance initiative progressing over the next year. They will share the best practices they've learned from encountering challenges during the initial phases of planning the company's governance project, as well as the unexpected ways in which the data governance solution they chose has been applied to solve many diverse problems across the organization. They will also discuss tips for planning and embarking upon an enterprise-wide data governance program, as well as what to expect at various project intervals - one year, two years, three years and beyond. Attendees will learn, amongst other key takeaways:
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Wednesday
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Data Quality Challenges in International Equities Geoffrey Kemmish, Acadian Asset Management, LLC This case study focuses on “lessons learned' from experience with identifier and time-series data problems in building and maintaining databases of historical International Equity data. With no global standards in force, or on the horizon, can we mix and match the alternative identifier schemes already in place to uniquely identify the entities - traded instruments, securities, issuers - that we are interested in? With no global standards in force, or on the horizon, can we compare financial results between companies? Or are we doomed to reinvent identifier schemes and charts of accounts over and over again? We will discuss how to resolve these issues, for organizations whose business survival depends on getting them right. |
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Designing Information Quality into the National Healthcare Identification System Tatiana Stebakova, National E-Health Transition Authority This case study describes how Australia’s National E-Health Transition Authority (NEHTA) implemented end-to-end data quality into its National Healthcare Identification system. The data quality strategy developed includes a DQ Framework, a DQ Capability Maturity, a DQ Implementation Roadmap, and specific DQ steps at each phase of the system's development life cycle We also share how we defined DQ requirements and embedded data quality into the business services' design and information architecture, and into the management process for the system's operations. The session will touch on challenges of the DQ Governance for federated community and our solution to overcome those difficulties. The session will also explain the role of NEHTA Data Quality Framework and describe its components, which include:
NEHTA's approach to defining and achieving Data Quality capability maturity will be also be shared. |
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| 3:00 - 4:00 KEYNOTE PANEL | ||||||||||||||||||||
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KEYNOTE
PANEL: This panel discussion will focus on real life experiences and challenges encountered by practitioners in starting and deploying data governance, data stewardship and information quality programs. Topics include:
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International
Association for Information and Data Quality (IAIDQ) Meeting All are invited to attend this meeting to get the latest updates on IAIDQ activities, 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 2010 goals and solicit your input and ideas for future plans. Add your voice to the conversation!! Attendees will receive a copy of the Information / Data Quality Salary and Job Satisfaction Report published in 2009 by IAIDQ and the IQ program at University of Arkansas at Little Rock. |
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