Tutorials and Afternoon Conference Sessions
November 18, 2013
| Monday November 18 7:00–6:00 |
Registration | ||||
| Monday November 18 7:00–8:30 |
Continental Breakfast | ||||
| 8:30 - 11:45 MORNING TUTORIALS | |||||
Monday |
AM1 - Data Governance 101: Organization, Roles, Policies,
and Processes David Loshin, President, Knowledge Integrity, Inc In this introductory tutorial we provide an overview of the policies, practices, and roles associated with initiating and sustaining a data governance program. An effective data governance demands practices and techniques for establishing the corporate value proposition for data governance, defining and approving data policies, and putting those policies into production. This requires effective communication of data policies and associated guidance across line-of-business boundaries, as well as repeatable processes for organizing data requirements for all key data concepts across the organization. Assessing the breadth of data requirements and expectations from across the line of business landscape is key, as is ensuring consistent observance of those requirements through the design, development, and implementation phases of the system development life cycle. In this tutorial we will also look at some practical operational aspects of data governance and stewardship, such as documenting data standards, harmonizing business term definitions and semantics, and methods for monitoring of observance to data expectations Attendees will learn about:
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Monday |
AM2 - Extending Project-focused Data Governance to the
Enterprise Kelle O'Neal, Managing Partner, First San Francisco Partners Did you start your Data Governance Program to support a specific department, project or regulatory requirement? Are you struggling to extend it to the enterprise? This session will provide tips and techniques for extending a project-oriented governance program to an enterprise initiative. We will review best practices, as well as examples and case studies to illustrate the concepts such as:
Attendees in this session will leave with a process and a roadmap to improve the effectiveness of governance by leveraging economies of scale and enterprise assets. |
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Monday |
AM3 - Data Governance for Big Data and Unstructured Data Malcolm Chisholm, President, AskGet Inc The emergence of Big Data as a major force since 2010 has resulted in many enterprises rethinking their approach to Data Management. At the same time, this has forced enterprises to think more clearly about how unstructured data (whether Big or not) has to be managed. The Data Governance challenges for Big Data and unstructured data are different to those for structured data in relational environments. This tutorial examines these challenges at a number of levels. These include (for both Big Data and unstructured data): dealing with sources, ensuring modeling of environments is done well, tracking what happens to data as it flows through environments, compensating for inadequacies in tools, semantic modeling for understanding of data, semantic modeling for distilling results of data processing, and integration with regular structured environments. General issues with lack of metadata for Big Data and unstructured data and the Data Governance response are described. Also discussed are approaches to getting the business to understand the urgent need for Data Governance in these areas, which are often seen as overwhelmingly the province of technology alone. Attendees will learn:
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Monday |
AM4 - Key Ingredients and Human Dynamics on How to be
Successful in Data Governance Len Silverston, President, Universal Data Models, LLC Len Silverston had the opportunity to help his client recognize such significant return on investment from their data governance program that they won the 2012 Data Governance Best Practice Award. A key to the success of this effort was understanding the personal, cultural, and political environment and consciously employing proven principles to enable success. The most successful data governance efforts usually share one thing in common: they developed and implemented effective strategies that provided fertile cultural and political ground for success. This seminar will first talk about key ingredients of data governance programs including how to:
Then the seminar will cover principles, tools, and techniques to empower participants in moving toward effective data governance. The instructor will share various insights, showing pitfalls of where data governance efforts can and have gone off course as well as sharing keys to successful data governance efforts. There will be interactive exercises where participants can practice handling difficult issues that commonly arise by applying principles leading to effective data governance. Participants of this seminar will gain:
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| 1:00 - 4:15 AFTERNOON TUTORIALS | |||||
Monday |
PM1 - How to Effectively Operationalize Data Stewards and
Your Data Governance Program Robert S. Seiner, President / Publisher, KIK Consulting / TDAN.com Data Stewards exist in your organization whether or not there is a formal Data Governance Program. These people may not know that they are stewards or they may not be formally recognized as such, but rest assured that there are people in your organization that have levels of accountability for how they define, produce and use data. This is a big advantage that not all organizations consider when delivering a Data Governance Program. This is one of the core tenets of a non-invasive approach to Data Governance. If Data Stewards already exist to one degree or another, this is something to leverage when starting to operationalize your program. In this half day session, Bob Seiner focuses on appropriate ways to identify data stewards, orient and onboard the data stewards to relevant aspects of your Data Governance Program, and getting data stewards to applying the core concepts of data governance in their daily activities. Attendees of this session will learn:
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Monday |
PM2 - How to Develop ROI and Value of Investment Metrics -
Demonstrating and Communicating Success Pat Branum, Enterprise Data Governance, Capital One Financial Eileen Koski, Director of Data Governance, North Shore LIJ Health & Hospital System The initial justifications for implementing Data Governance and Stewardship programs are often based on known data issues that have caused business problems for an organization. A program that successfully solves real business problems by identifying and addressing data issues, may still struggle in the long run if they cannot effectively demonstrate and communicate their accomplishments within their organization. The key to demonstrating success - and in particular to maintaining enthusiasm over time - is to derive, document and appropriately communicate persuasive metrics on Return On Investment (ROI) or Value Of Investment (VOI). While it is easy to understand why metrics are important, it is not always easy to figure out how to derive them or how, when and to whom to communicate them. Through examples and in-class exercises, this session will teach participants how to translate success into persuasive metrics, as well as discussing strategies for effective communication. Topics:
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Monday |
PM3 - Effective Data Governance for Master Data Management Malcolm Chisholm, President, AskGet Inc Master Data Management (MDM) continues to be a challenge for many enterprises. Over the past few years there has been a growing awareness that Data Governance is a prerequisite for successful MDM and that Data Governance translate into well-run operational practices that are capable of evolving with the business. This tutorial focuses on the essential areas of Data Governance that must be established for MDM and how to overcome the challenges of operationalization. The complex and multi-disciplinary nature of MDM is addressed in terms of governance. Attention is also paid to qualitative differences in governance needed for different MDM entities such as customer, product, account, financial instrument, and reference data. Some level of tool support is needed for Data Governance to be successful for MDM, and the nature of this tool support is described. Additionally, the different roles involved in Data Governance are outlined. This is particularly important for MDM as there are widely disparate views on what a Data Steward, an SME, a Data Manager, etc. are, and lack of role clarity is known to be a significant obstacle for MDM implementations. Attendees will learn:
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Monday |
PM4 - How to Sustain Data Governance John Ladley, President, IMCue Solutions Now you have data governance up and running. Now what? Is it self sustaining? (no) Is it hard to keep going? (yes). This session will cover the major roadblocks to keeping Data Governance programs running after they have been implemented.
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| 4:30 - 5:20 AFTERNOON CONFERENCE SESSIONS | |||||
Monday |
Basel II and the Implications for Data Management and Data Quality Bhaskar Kuppusamy, Managing Partner, Aikya Incorporated Basel II is a regulatory compliance, international standard, and best practice that places guards against financial and operational risks faced by banks. This presentation discusses the data management implications, best practices, and lessons learnt from our experience. Topics include:
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Monday |
7 Key Materials for Building a Data Governance Shop -
Year One at the University of Pittsburgh Medical Center Matthew Slavonic, Lead Data Governance Analyst, UPMC Susan Majcher, Senior Data Governance Analyst, UPMC There are many key materials when building a workshop that can be compared to what it takes to build a Data Governance Program. In this session we will present how the Data Governance Program at UPMC used these 7 materials when building the program during its first year:
Each one of these materials is important to help establish a strong, reliable, and scalable Data Governance Program. These materials can also be simply categorized under: Each one of these materials is important to help establish a strong, reliable, and scalable Data Governance Program. These materials can also be simply categorized under:
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Monday |
Metadata as a Data Governance Enabler David Kowalski, Senior VP, Bank of America Providing minimally intrusive and maximally effective data governance within large, complex organizations, we encounter a number of special challenges. Conflicting business and technical terminology, inadequate documentation of data sources and an often legitimate need for different lines of business to manage data in different ways are just some of the contributors to a complex landscape in which the implementation and governance of a coherent Enterprise-level data management program can be highly problematic. Bank of America has implemented an Enterprise Data Management Policy with associated Standards to enact a federated approach to coordinating data management across 23 separate business units across the Bank. At present, these standards address requirements to:
The last of these is at the heart of our approach. A centralized, carefully governed metadata repository provides a trusted source for much of the information necessary to govern our data practices as well as providing a true Rosetta stone for simplifying and coordinating our terminology across the organization. Moreover, as we further develop strategies to leverage the metadata, we are regularly finding ways in which this allows us to meet regulatory requirements, reduce operational inefficiencies and better drive the analytic processes which drive revenue growth. Level of Audience: |
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