Conference Sessions - June 25, 2014
| Wednesday June 25 7:30–8:30 |
Registration and Continental Breakfast | ||||||||||||||||||||||||||
 8:00
- 8:50 CONCURRENT SESSIONS |
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Wednesday
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Data
Quality Testing - Whose job is it REALLY?? Sherry Michaels, Data Quality Program Manager, The Hartford Whose job should it REALLY be to test the data quality rules in your organization? In this session, we’ll look at the need to have business data experts on the front line of the testing process. Whether you call them data quality analysts, data scientists, data stewards or another fancy industry name, the fact remains the same: the people testing your data quality rules and analyzing the outcome of those tests should always be someone with expert knowledge of the data and a clear understanding of how it is used within the business and across the organization. Throughout the session, we’ll discuss various practices and beliefs found within the data governance process today when it comes to data quality testing and review scenarios that will illustrate the benefit of having business data experts directly involved and responsible when determining whether or not your data is fit for purpose. Level of Audience |
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Wednesday
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Cross-Functional Collaboration
to Provide Aligned Business Data to the Enterprise Lisa Cutler-Farwig, Master Data Project Manager, Schlumberger As Schlumberger grew to over 120,000 employees, the ability to cobble together cross-functional performance indicators became more difficult. Historically, Personnel and Finance data drove data organization in most other applications across our enterprise. Issues arose because there was no overall governance of data: Finance vs. Personnel data followers had completely different data organization and levels of granularity. This is our story of overcoming years of siloed data management to implement an enterprise wide solution.
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Wednesday
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Achieving
Successful, Cost-effective Customer MDM: How to Shrink Time and Costs without
Sacrificing Quality Michael Ott, Sr. VP, Innovative Systems, Inc. It’s no surprise that organizations are considering and undertaking Customer MDM initiatives. The reasons for doing so are many, including cost reduction, increased revenue creation, reduced compliance cost and risk, improved organizational efficiency, and better organizational decision‐making. As numerous as the benefits are, many organizations have yet to tackle MDM initiatives because of their perceived size and complexity. The good news is that much of the time and investment previously thought to be required in these types of initiatives is no longer always necessary. Advances in processes, methodologies, and technologies allow many of the appropriate steps required in the full project life cycle to be dramatically shortened, enabling organizations to establish high quality MDM repositories at a fraction of the time. This presentation will walk through the important components of successful Customer MDM projects, highlighting those areas where organizations can achieve significant time and cost savings. Takeaways will include:
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Wednesday
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Project
Management & Data Governance – Are You Really in Control? Kiran Gill, Senior Strategic Consultant, Trillium Software This session provides a step by step guide to embedding data governance and data management processes into project management to ensure project teams efficiently control and leverage your organization’s most critical asset – its data. Project management is the discipline of “planning, organizing, motivating, and controlling resources to achieve specific goals,” and its success is highly dependent on the quality and management of data. Project management teams introduce immense risks when they fail to recognize and address a project’s data constraints, restrictions and requirements, as well as the amount of time needed to prepare data to ensure it fits the needs of a project. The presentation highlights data risk management processes, data requirements assessments, data analyses, data planning methods, and other key activities that are commonly absent in project management but critical to its success. This session is based on data trends observed in real project management environments within many global financial, retail, utilities and healthcare organizations that the presenter has worked with. The presentation provides first hand data management observations in projects during the 5 stages:
The audience can expect a step by step guide to help achieve optimum levels of data governance, data control and data risk management in the project management process. This is achieved by interweaving and embedding data governance in project management methodology, which really will help you regain control of data within successfully managed projects. Level of Audience |
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Wednesday
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PANEL: Addressing
Data Governance Challenges in the Financial Sector Moderator: Steve Zagoudis, CEO, MetaGovernance Inc Panelists: Barbara Deemer, Chief Data Steward, Sallie Mae Peter Kapur, Director Data Governance, Quality and Analytics, The Depository Trust and Clearing Corporation (DTCC) Harold Finkel, Managing Director, Business Data Management, TIAA-CREF Kevin Shannon, VP Data Strategy Operations, Standard and Poor’s This panel will address the unique challenges of the financial sector in implementing data governance programs Topics include:
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| 8:50 - 9:05 Room Change | |||||||||||||||||||||||||||
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Wednesday |
KEYNOTE: Back of the Napkin Data Monetization Anne Buff, SAS Best Practices Thought Leader, SAS The simplicity of “back of the napkin” business ideas allows us to put our best thoughts on paper in quick, visual representations exposing hidden answers to questions that have plagued us for longer than we want to admit. Determining the value of data is no different. “Data is a corporate asset” has achieved platitude status yet companies are still looking for the answer to the age old question of “How much is our data worth?” In this presentation we’ll clear up the confusion around Data Monetization, offering an authoritative definition and illustrating examples of how to sketch it out. We’ll also examine the value of quantifying the financial worth of data, review key considerations of monetizing data and suggest ways of getting—and keeping—data front and center on the executive priority list. Level of Audience: |
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| 9:35 - 10:15 Coffee Break & Exhibits Open | |||||||||||||||||||||||||||
| 10:15
- 10:45 DATA GOVERNANCE AND IQ SOLUTIONS |
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Wednesday
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Locate and Exterminate – Find the Hidden Factories in Your Business Kiran Gill, Senior Strategic Consultant, Trillium Software Lean Data Governance is the application of Lean methodology to data governance using key Lean methodologies. This approach can help your business to prevent and eliminate wasteful data management processes and wasteful or inefficient activity. Lean Data Governance helps organisations to deliver robust, reliable and timely outputs to their internal customers by locating and eliminating Hidden Factories. The term “Hidden Factory” is used to describe areas within the business that are visible to the eye, but have unseen processes running in the background. These activities are not transparent, they’re very wasteful and they run a high risk of duplication of effort. Lean Data Governance feeds the process of identifying and exposing these Hidden Factories, allowing the business to replace these with more transparent and efficient operations. This session will detail the process of locating and exterminating these factories, using Trillium’s Data Governance disciplines leveraged by Trillium Strategic Consulting. We will walk through the process of finding these factories, working out what they do and formulating a plan to exterminate. We will explore how these inefficient operations can be replaced with Visible Factories that promote success and growth. Audience Level: |
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Wednesday
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Achieving Data Quality with Infogix Solutions Chris Reed, Solutions Consultant, Infogix Jay Shah, Product Manager, Infogix, Inc. Business operations today depend on accurate, consistent, and reliable data to ensure that processes are running effectively and accurately. Infogix Assure provides the capabilities to implement automated information controls that detect data errors across business operations and the enterprise. In this session, Infogix will review how the Infogix Assure Data Quality Module helps assess the quality of operational data, as it dynamically moves throughout processes, enabling data quality controls. Audience Level: |
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Wednesday
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Improving Information Governance through Clarity and Collaboration Scott Braker-Abene, Director Solution Management, Information Management, SAP Traci Sullivan, Sr. Solution Engineer, SAP Good information governance can be a complex undertaking, but one thing is clear – it depends on a 360-degree visual framework used collaboratively by management, IT organizations, and business users for the entire data lifecycle. SAP’s Enterprise Information Management portfolio helps users to create a collaborative framework for the entire information governance lifecycle. They enable a direct line of sight from the source of data to its impact on the business. Audience Level: |
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Wednesday
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Why Product Information Management? Role of Data Governance & Data Quality in Successful Product Information Management Initiatives Raman Parthasarathy, Vice President of Product Strategy, Riversand Technologies Kelle O'Neal, Managing Partner, First San Francisco Partners Organizations such as Retailers, Manufacturers and others dealing with Product Data as a key data domain are increasingly looking at Product Information Management (PIM). Some of business benefits of PIM include faster new product introductions, increased productivity in managing product master data, clear and consistent product data across different channels resulting in better customer experience and increased sales. From a data perspective, PIM initiatives involve product data acquisition internally and externally through business partners followed by data management & enrichment through complex business process workflows supported by data governance & stewardship. The range of data spans from internal & structured to external and unstructured content. Key understanding and focus on Data Quality Management (DQM) as well as Data Governance (DG) becomes an important imperative for the overall success of the PIM program and in turn resulting in increased business value & impact. In this session we will cover:
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| 10:45 - 11:00 Room Change | |||||||||||||||||||||||||||
| 11:00 - 11:50 CONCURRENT SESSIONS | |||||||||||||||||||||||||||
Wednesday
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Business Driven
Data Governance– Led by Business in Partnership with Technology Peter Kapur, Director Data Governance, Quality and Analytics, The Depository Trust and Clearing Corporation (DTCC) We will discuss several initiatives in DTCC that were successful using the principles of creating Lean but inclusive Governance Structures that are Business driven in partnership with Technology. At DTCC, we apply business value criteria to determine what business area or data needs to be managed beyond a localized view. The Data Governance Council and Data Governance Advisory are Business led but inclusive of all functional areas of the company and cater to stakeholder needs. The DTCC approach:
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Wednesday
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Identifier
Resolution is the Ultimate Answer to Increasing Data Quality as Well as
Reducing its Cost Peter Benson, Executive Director, ECCMA Identifiers are literally the keys to unlocking the value in data. From telephone numbers to account numbers, part numbers, tax identification numbers, social security numbers and passport numbers through to the new Legal Entity Identifier (LEI); identifiers are the most valuable yet the most fragile of all data elements. Storing, using or distributing an identifier that can be validated is the key to improving data quality and decreasing risk. Identifiers are also copyright and using an identifier without knowing if its use is authorized can create substantial hidden financial liabilities. “Quality Identifier Resolution” is a simple process that can be used to automate the identification of the owner of an identifier as well as provide automated validation and resolution of the identifier itself. Learn how to recognize a quality identifier and how to use ISO 22745 to request resolution of quality identifiers to authoritative master data. Learn how to create and publish your own quality identifiers as well as how to use ISO 22745 to provide quality identifier resolution services. Level of Audience |
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Wednesday
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Achieving Data Governance in the Big Data Paradigm Joe Caserta, President, Caserta Concepts Data Governance in the Big Data paradigm is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient. It supports high, and strives to prevent low, data quality, ensuring that the data can be trusted -- and people will be held accountable for any adverse event that may happen. This presentation explains the “agile” data culture where we:
There is also a look at the increased importance of Data Security – determining who sees what – with an overview of products currently available to ensure and support a secure environment. Level of Audience |
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Wednesday
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Characteristics of a Maturing Data Governance Program Mary Anne Hopper, Management Consultant, SAS Successful Data Governance programs have some commonalities – planning, monitoring, measurement and most importantly, Data Management outcomes. Whether kicking off a program, breathing life back into a faltering program, or improving current processes, there are some actionable steps that are critical to success. This class will explore those success factors, the importance of Data Management, and what it means to mature a Data Governance program. Attendees will learn:
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Wednesday
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Data Governance in the Real World Michael Atkin, Managing Director, EDM Council Data governance is the backbone of a successful data management program. It is about setting standards, defining rules and implementing an oversight process to ensure adherence to established data policy. The goal is to ensure trust and confidence among consumers that the data they are relying on for business processing and decision making is precisely what they expect it to be, without the need for manual reconciliation or reliance on data transformation processes. This is achieved via the adoption of standards. Standards are governed by policy. Policy is established by executive management and enforced by audit. Attend this session and learn how to:
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| 11:50 - 1:15 LUNCH | |||||||||||||||||||||||||||
| 1:15 - 2:05 CONCURRENT SESSIONS | |||||||||||||||||||||||||||
Wednesday
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Implementing Sustainable Data Governance at Cerveceria Nacional-SABMiller Ecuador Maria Suarez, MDM Manager, Cerveceria Nacional - Sabmiller Ecuador The presentation will show how we implemented our Data Governance Program from nothing, in a company were no one knows or understands master data. This has resulted in our team being recognized as a value added team that develop solutions to the business The presentation details how the master data model evolved from a non-value process to a core business process offering key support in every functional area at Cerveceria Nacional, Subsidiary SABMiller Plc. Topics include:
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Wednesday
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Integrating Data
Governance and Data Exploration Ted Chila, Director of Data Services, Broadcast Music Inc. Today, most enterprises have multiple groups of sophisticated users of outside of IT consuming the enterprise data asset. They want to perform complex data exploration on enterprise data (ODS/EDW), external data sets, and their own ad-hoc data artifacts. This presentation discusses the challenges of providing the means to use these data together while maintaining the integrity of the core enterprise data asset. Solution approaches incorporate hardware and software, data architecture, and the expansion of data governance process and roles into new areas. Topics include:
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Wednesday
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Beauty is in the Eye of the Beholder: Measuring the Benefits of Governance Michael Nicosia, Director, Corp Finance Data & Integration, TIAA-CREF Erik Ferrone, Manager, TIAA-CREF "It" can be relative to something else; "It" can be what is perceived; "It" can be what you state it as; "It" can vary by person, by group, by area, etc. – so, what is "it"? The "It" in this case refers to value; more specifically the benefits that governance can bring to an organization. Even if you are a seasoned governance practitioner or someone just starting the journey, the question you wrestle with most often is "how do I measure the value of governance?" The answer to this question, unfortunately, is not so simple. The value of governance – aka benefits – is often hard to define and even harder (at times) to measure in a way that is meaningful to a broad group of stakeholders – but not impossible! This session will provide insight into:
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Wednesday
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Data Asset
Performance Management and Governance Robert Guberud, VP, IQM and Governance Practice, Stream Integration This presentation introduces the concept of data asset performance measurement - twenty key indicators across six different decision areas, a set of business intelligence solutions to be used by innovative companies to drive greater information asset valuation and governance. These solutions reflect the insight that the most valuable information in data governance related decision-making is concentrated in a relatively small number of meta information asset "sweet spots", i.e. nodes in a corporation's analysis of the information value chain. Decision areas are organized by six major functions that drive different slices of performance. Learn how to implement these core competencies for data asset management and governance program success factors. Starting with critical data element support for corporate performance indicators and vital business functions, each area considers key challenges and means to measure success in areas such as Best Practice Production, Data Quality Operations, Data Competence, Learning and Growth, and also looking at data asset financial management and information valuation. Level of Audience |
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Wednesday
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PANEL: Tips from the Trenches-Lessons Learned from Successful
Practitioners Moderator: Michael Scofield, Assistant Professor, Loma Linda University Panelists: Pablo Riboldi, MDM & Governance Engineer, LDS Church Michele Koch, Director, Enterprise Data Management, Sallie Mae Jose Solera, Director IT Enterprise Services & PMO, Railinc Mark Nadeau, Director, Global Marketing Technology and Data Governance Office, Schneider Electric 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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| 2:05 - 2:20 Room Change | |||||||||||||||||||||||||||
| 2:20
- 3:10 CONCURRENT SESSIONS |
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Wednesday
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Hope is not a Strategy: How to use Proven Sales Techniques to Maintain the Commitment in your Data Governance Program Kelle O'Neal, Managing Partner, First San Francisco Partners It's obvious that data is a valuable corporate asset, so why aren't the executives supporting your data strategy? One of the biggest challenges behind establishing and sustaining a Data Governance Program is getting and maintaining the commitment of key stakeholders. A successful way to gain this involvement is to think about this process as a sales process. What do you need to do to convince these stakeholders to "buy" your Program? In this session we will use well-known sales techniques to demonstrate:
Using specific examples from different company programs, we will demonstrate these sales techniques from the viewpoint of a Data Governance leader who is responsible to build and execute the program. Level of Audience |
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Wednesday
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Starting and
evolving a Data Quality Program at University of British Columbia George Firican, University of British Columbia, Data Quality Manager It is a fact that poor quality data is costing large amounts of money to institutions all over the world. Within the fundraising and alumni relations domain this might equate into potentially lost prospects, donors, donations, alumni engagements, and resources needlessly spent on redundant procedures, etc. The University of British Columbia’s (UBC) "Start an Evolution" campaign aims to raise $1.5 billion dollars for students, research and community engagement and to double the number of alumni involved annually in the life of the university by 2015. As such, a Data Quality Program is crucial in supporting this goal. This presentation will show how UBC’s Development and Alumni Portfolio started and evolved a Data Quality Program, its success stories and lessons learned. You will learn:
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Wednesday
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Metrics Required
For Successful Data Governance Dave Borean, VP Technology, InfoTrellis This season will discuss metrics that must be gathered and reported on to be successful with master data management and the emerging discipline of big data management. Examples of metrics include data quality (issue discovery and backlogs), data change, data composition, data stewardship and data consumption trends. Real-world case studies and examples will be presented along with how these metrics enable various stakeholders, including data governance councils, to better manage the data such as increasing quality and decreasing TCO. This session will cover:
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Wednesday
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Engaging
Users Better and Promoting Statistical Data Quality Doreen Kasozi, Senior Officer Standards, Uganda Bureau of Statistics In Uganda, the demand for statistics has grown in response to social, economic, environmental and political developments in the country especially over the last 15 years. To respond to these demands, Uganda Bureau of Statistics (UBOS) and respective producers generate various statistics products through collection, analysis and coordination of socio-economic data. Among these are key development indicators that inform the national and regional development agenda, as well as international development frameworks for example the MDGs, IMF, World Bank etc. However, in spite of existing user engagements and successful partnerships established in statistical work, the Bureau still faces a number of challenges that affect the quality and usability of statistical information This presentation will focus on the challenges of how we are resolving these issues and promoting statistical data quality. This includes:
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Wednesday
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PANEL: Is Data Quality Really a Discipline? Although everyone agrees that poor data quality is a problem and needs to be addressed few organizations have dedicated data quality teams. For some- information quality is a part of another job and many analysts don’t have the authority to effectively make changes and get the business more involved. Our panel will address the following and provide recommendations how to succeed in data quality and make data quality a priority :
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| 3:10 - 3:30 Coffee Break | |||||||||||||||||||||||||||
| 3:30 - 4:20 KEYNOTE | |||||||||||||||||||||||||||
Wednesday
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KEYNOTE: Privacy Engineering and Data Governance Michelle Dennedy, VP Chief Privacy Officer, McAfee Thomas Finneran, Principal Consultant, IDennedy Project The earth is not flat and privacy is not dead. The presentation is for data governance and data management practitioners (and their management and support personnel) to be exposed to a systematic engineering approach to develop privacy policies based upon enterprise goals and appropriate government regulations. We will present a privacy requirements checklist that will be used to aid data stewards to include privacy demands along with business requirements into system development use cases. We will also discuss the roles that will ensure privacy compliance, including the roles of data collection stewards and data use stewards. Data collection stewards will, among other duties, classify data attributes within their area of responsibility, as to data sensitivity and whether encryption is needed. The data use stewards will ensure that reports and other outputs comply with government and enterprise policies. A quality assurance checklist that will be used throughout the development process will be discussed.
Organizational aspects of privacy engineering will be discussed including Privacy Readiness Assessment and alignment of a privacy organization and the data governance. Much of the content will be based upon the new book “The Privacy Engineer’s Manifesto: Getting from Policy to Code to QA to Value” by Michelle Finneran Dennedy, Thomas R Finneran, and Jonathan Fox. Level of Audience |
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Wednesday
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Data Governance and Health Care Special Interest Group DGPO Data Governance Health Care SIG Facilitators Eileen Koski, Director, Data Governance, North Shore LIJ Health System George Yuhasz, Director, Data Process & Governance, HealthNow New York Inc. Data Governance and Data Quality Professionals from different areas of healthcare, including payers, providers and others, have recently come together to form the DGPO Data Governance and Health Care Special Interest Group (SIG). The purpose of this SIG is to provide a forum where people in the healthcare industry can interact with their peers and learn more about techniques and approaches that may be valuable in their own environments, particularly related to how Data Governance and Stewardship can help them address those needs. The DGPO invites everyone attending the conference and stewardship seminar to attend the first in-person meeting of the HealthCare SIG. We encourage you to bring your questions, concerns, unique perspectives and your curiosity to the table and join us as we continue to grow the SIG and find new ways to support each other in our journey towards better health care through better data! Level of Audience |
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