Pre-Conference Tutorials and Conference Sessions -
June 23, 2014

 

Monday
June 23
7:30–8:30
Registration and Continental Breakfast
8:30 - 11:45 MORNING TUTORIALS

Monday
June 23
8:30-11:45

 

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T1: Data Governance 101: Organization, Roles, Policies, and Processes 
David Loshin, President, Knowledge Integrity

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:

  • Drivers for data governance
  • Organizational operating model for data governance
  • Roles and responsibilities
  • Collecting data requirements
  • Processes for defining and approving data policies
  • Oversight of common reference data concepts
  • Operational data stewardship

Level of Audience
Introductory

Speaker:
David Loshin David Loshin
President
Knowledge Integrity

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Monday
June 23
8:30-11:45

 

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T2: Governance of the Business Glossary 
Lowell Fryman, Sr. Principal, Aspen Information Solutions

A Business Glossary is not a static list or word document of business terms and definitions. It is a critical Data Governance tool for exposing authoritative content from DG initiatives and used to communicate understanding and clarity across the enterprise. A critical objective for DG is to maximize the understanding of the core business concepts and terminology of the organization. A business glossary can connect workers across the enterprise to critical business information they can trust, helping to eliminate misunderstandings that cause lost time, lost opportunities and lost revenue. Creating great definitions and term names will aid significantly in enabling search capabilities.

Good Governance processes and standards are critical for many enterprises that are:

  • Organized geographically introducing global enterprise semantic   differences
  • Organized around Products or Vertically
  • Human semantic differences created by the many languages used
  • Business Unit semantic differences
  • Mergers and Acquisitions introduce semantic differences

This tutorial will be helpful for data management and Governance professionals that have been challenged with any of the following issues:

  • Too many acronyms that few understand
  • Business Intelligence, BPM and KPI ambiguity
  • Legal and compliance regulations (such as TART)
  • Enterprise or international projects like CDI/MDM
  • Multiple glossaries and technologies across the organizations
  • Conflict between Business and IT

From this Tutorial you will learn through workshop examples and interactions:

  • Methods for establishing the Governance organizations, standards and best practices
  • How to leverage your existing Governance team and processes
  • How to create structured definition standards and how to name terms 
  • Techniques for defining the Glossary categories, taxonomy and leverage your firms taxonomy
  • Techniques to get your Glossary populated
  • Methods to promote the usage and sustainability across the enterprise
  • Alternative Governance models to find one that fits your organizations needs

Level of Audience
Introductory

Speaker:
Lowell Fryman Lowell Fryman
Sr. Principal
Aspen Information Solutions

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Monday
June 23
8:30-11:45

 

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T3: How to Design, Develop, and Implement an Award Winning Enterprise DQ Program 
Michele Koch, Director, Enterprise Data Management, Sallie Mae
Barbara Deemer, Chief Data Steward, Sallie Mae

In this tutorial, Michele Koch (DG Program Director) and Barbara Deemer (Chief Data Steward) will provide an overview of Sallie Mae’s approach to designing and implementing an award winning enterprise DQ Program.  Attendees will learn about their grass root tactics, the development of a DQ Cookbook and how they engaged their data stewards to become data approvers for the formal DQ Program.  This tutorial will also provide a detailed, step-by-step account of Sallie Mae’s successful approach to developing business value calculations to quantify the impacts to generating revenue and avoiding costs.  Topics that will be covered include:
  • Developing your vision, mission and guiding principles
  • Developing your organizational structures and their roles and responsibilities
  • Engaging the DG Council and identifying business approvers
  • Developing your services engagement model
  • Developing your framework and methodology
  • Deriving business value calculations
  • Tracking potential versus actual business value

Our hope is that our lessons learned with help others in this area since we know how difficult determining metrics can be. 

Level of Audience
Introductory

Speakers:
Michele Koch Michele Koch
Director, Enterprise Data Management
Sallie Mae

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  Barbara Deemer Barbara Deemer
Chief Data Steward
Sallie Mae

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Monday
June 23
8:30-11:45

 

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T4: How to Develop ROI and Value of Investment Metrics - Demonstrating and Communicating Success 
Eileen Koski, Director, Data Governance, North Shore LIJ Health 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 addressing data issues, may still struggle to maintain support 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 Value Of Investment and Return On Investment (VOI/ROI). 

While it is easy to understand why VOI/ROI 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 VOI/ROI metrics, as well as discussing strategies for effective communication.

  • When to use VOI, ROI or both
  • Fundamentals – Choosing projects wisely: establishing, sponsorship, intended business impact, goals and accountability
  • Internal vs. external measures and benchmarks
  • Nuts and bolts – creating formulas, calculating and validating results
  • Communicating VOI/ROI – how, when and to whom
  • Using VOI/ROI to build or strengthen bridges

Level of Audience
Intermediate

Speaker:
Eileen Koski Eileen Koski
Director, Data Governance
North Shore LIJ Health System

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Monday
June 23
8:30-11:45

 

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T5: Governing Master Data: A Practical Tutorial Applying Data Governance to MDM 
Pablo Riboldi, MDM & Governance Engineer, LDS Church

Do you have a MDM solution without governance?
Do you have a DG program without MDM?
Do you have neither?
Do you have both MDM and DG but not working together?
If you answer “Yes” to any of the above questions, this tutorial is for you!

Some of the first questions that come up when starting a Data Governance program is “What should we govern?” and “How should we govern the data?”

In this tutorial you will find out how to harness the synergies between Data Governance and Master Data Management at your organization.

You will learn:

  • How to set up MDM easily (and cheap)• How to benefit MDM with good data governance
  • How to identify the main subject areas for your MDM solution
  • How the Data Governance program is strengthen with a MDM solution
  • How to support and promote both throughout the enterprise
  • How to adjust an existing MDM program to increase its value
  • How to prove the value of MDM and Governance to the enterprise.

Level of Audience
Introductory

Speaker:
Pablo Riboldi Pablo Riboldi
MDM & Governance Engineer
LDS Church

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Monday
June 23
8:30-11:45

 

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T6: Governing Big Data
Sunil Soares, Founder and Managing Partner, Information Asset LLC

This tutorial will provide an overview of Big Data Governance to business and IT practitioners. It will discuss the convergence of Big Data and Data Governance.

The following topics will be discussed:

  • Getting Started
    • Introduction to Big Data Governance
    • Big Data Governance framework
  • Big Data Governance disciplines
    • Organizing for Big Data Governance
    • Metadata
    • Privacy
    • Data Quality
    • Business Process Integration
    • Master Data Integration
    • Managing the lifecycle of Big Data
  • Governance of Big Data Types
    • Web and Social Media
    • Machine-to-Machine data
    • Big Transaction data
    • Human-Generated data
    • Biometrics
  •  Big Data Reference Architecture

Level of Audience
Introductory

Speaker:
Sunil Soares Sunil Soares
Founder and Managing Partner
Information Asset LLC

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1:00 - 4:15 AFTERNOON TUTORIALS

Monday
June 23
1:00–4:15

 

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T7: Stewards, Stewardship and the Stewarding of Data
Robert S. Seiner, President/Publisher, KIK Consulting / TDAN.com

There are several ways to operationalize Data Stewards. The issue always comes down to what is the best fit for the existing culture of the organization. There are many things to consider – the responsibilities of the Data Steward, where the Stewards reside, who manages the Stewards, what kind of Stewards should there be, and perhaps the most important question – how do we get our Stewards to do what Stewards do? This presentation will answer all of those questions.

In this half-day session Bob Seiner will compare and contrast several different approaches to resolving the Data Steward issue and help the attendees to select the approach that is best for them. If you didn’t know there were multiple approaches or never took the time to investigate the pros and cons of the different approaches, this session is for you.

In this session Bob will discuss:

  • How to Define the Data Steward for Your Organization
  • How to Improve Awareness of Steward Impact on the Organization and Quality of Data
  • How to Identify Where Stewards Reside and Who They Represent
  • How to Compare and Contrast Different Approaches to Stewardship
  • How to Select the Approach that Fits in Best with the Existing Culture

Level of Audience
Introductory

Speaker:
Robert S. Seiner Robert S. Seiner
President/Publisher
KIK Consulting / TDAN.com

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Monday
June 23
1:00–4:15

 

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T8: An In-Depth Tutorial on Data Governance Software Tools
Sunil Soares, Founder and Managing Partner, Information Asset LLC

Data Governance involves a strong focus on people and process. However, software tools are becoming increasingly mature and should form part of every Data Governance program. There are a dizzying array of offerings, and vendors confuse matters by slapping the term "Data Governance" on all types of tools. This session will be presented in a vendor-agnostic manner but will review offerings from Collibra, Data Advantage Group, Embarcadero, Global IDs, IBM, Informatica, Orchestra Networks, SAP, SAS, Semarchy, Trillium, and others.

In this session, we will do the following:

  • Define "Data Governance" tools
  • Review a reference architecture for Data Governance software
  • Consider vendor-agnostic evaluation criteria for tools
  • Discuss the pros and cons of offerings from different vendors
  • Demonstrate software tools for a hands-on perspective
  • Understand how data policies and standards can be implemented in Data Governance tools
  • Learn how tools can implement a Data Governance dashboard
  • Become familiar with the interplay between business terms, metadata, reference data, data quality and master data management

Level of Audience
Intermediate

Speaker:
Sunil Soares Sunil Soares
Founder and Managing Partner
Information Asset LLC

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Monday
June 23
1:00–4:15

 

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T9: Using Data Profiling for Proactive Data Quality Improvement
David Plotkin, Advisory Consultant, EMC

As your company moves to proactive data quality improvement, data profiling provides a robust methodology and toolset to discover quality issues before your customers do. This presentation discusses the advantages of proactive data quality improvement, how to set up an infrastructure (including stewardship) to support the effort, the gathering and documentation of data quality rules, what data profiling is, using data profiling for existing and new data elements, and what to do when you do find data quality issues.

You will learn:

  • What data quality issues profiling helps you find
  • How to build templates for collecting data quality rules and a repository to store those rules in.
  • The pitfalls of working with the business people-what works and what doesn’t.
  • An iterative methodology for finding and then reviewing the results of data profiling.
  • Implementing data quality rules during a data load

Level of Audience
Introductory

Speaker:
David Plotkin David Plotkin
Advisory Consultant
EMC

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Monday
June 23
1:00–4:15

 

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T10: Enforcement & Accountability for Compliance & Governance: Metrics, Mind Set & Magyver
Daragh O Brien, Managing Director, Castlebridge Associates
Joy Medved, Strategy Consultant, Paradata Consulting, LLC

Connecting the dots between Policy, Accountability, and Actions in Data Governance can be challenging. This tutorial provides an intensive intermediate-to-advanced look at real world challenges faced when implementing and managing an Enterprise Data Governance program. Specifically, participants will learn how to develop their own tools and techniques to ensure efficient change management and effective compliance enforcement. We will look at how automation is not about technology, but rather about the Data. We will also tackle the challenge of DG vs. DQ division of responsibilities.

Participants will learn:

  • The pros and cons of three enforcement methods (Automation, Manual, Hybrid)
  • How to apply Agile and Entrepreneurial approaches to develop enforcement methods (or “How can we Magyver this?”)
  • How to ensure tangible links between DG policies and quality data outcomes
  • How to drive positive information quality practices and outcomes in your organization
  • The myth of self-certification in DG enforcement
  • Understanding the Segregation of Duties (Authority & Accountability)
  • The importance of metrics, including the psychological significance of Null values

Level of Audience
Advanced

Speakers:
Daragh O Brien Daragh O Brien
Managing Director
Castlebridge Associates

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  Joy Medved Joy Medved
Strategy Consultant
Paradata Consulting, LLC

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Monday
June 23
1:00–4:15

 

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T11: How to Develop an Effective Metadata Governance Strategy
Steve Zagoudis, CEO, MetaGovernance Inc

Effective Metadata Governance is a very strong enabler of organizational efficiency and transformation.  Yet most organizations fail to leverage this valuable asset through ineffective governance approaches. Metadata Governance is an emerging discipline that in based on the advancements in Data Management, Data Governance, Information Governance and Enterprise Architecture.  Metadata can be used to define all aspects of today’s organizations. Metadata management solutions often stovepipe metadata so the true value is lost. This tutorial will provide a view of an organization from a metadata perspective and discuss the need, value, and approaches to Metadata Governance. Typical business transactions and system implementations will be used to define the metadata concepts.  Basic metadata relationships will be explored. The metadata components of effective Data Governance implementation will be outlined along with the governance policies and approaches required.

This tutorial will provide the following:

  • A detailed discussion on Metadata Governance
  • Understanding the metadata characteristics across all five layers of the Enterprise Architecture
  • The fundamental metadata and relationships inherent in Data Governance and Information Governance
  • Requirements for a metadata repository
  • Policies, logistics and roles for effective Metadata Governance.

Level of Audience
Intermediate

Speaker:
Steve Zagoudis Steve Zagoudis
CEO
MetaGovernance Inc

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Monday
June 23
1:00–4:15

 

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T12: Data Quality Strategy and Architecture for Data Governance 
David Loshin, President, Knowledge Integrity

Devising a Data Quality Strategy and Architecture to satisfy the needs of an enterprise data governance program means transitioning from a culture of after-the-fact cleansing into one focused on deploying best practices in alignment with enterprise data policies. That strategy includes proactive assessment, measurement, inspection, monitoring, notification, tracking, and resolution of data quality issues. Identifying and implementing the associated componentry coupled with best practices in data quality and governance will help retool existing workflow processes with automated systems that can help reduce the need for manual data inspection while rapidly alerting data stewards to identified issues.

This tutorial looks at leveraging an organization’s existing data management infrastructure, available development tools, and practical data quality best practices to develop a formal framework for data quality management that organizes practices for:

  • Data quality measurement and reporting: Enabling and invoking services to validate data against data rules and report anomalies and data flaws, both through notifications and through scorecards.
  • User data usability requirements management: Soliciting and managing data use requirements and business rules in concert with defined policies.
  • Standardized data validation: Validate existing processes while integrating services for data verification as part of the system development life cycle.
  • Source data quality assessment: Source data assessment and evaluation of data issues to identify potential data quality rules.
  • Incident management: Standardized approaches to data quality incident management (reporting, analysis/evaluation, prioritization, remediation, tracking).

Level of Audience
Intermediate

Speaker:
David Loshin David Loshin
President
Knowledge Integrity

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Arrow4:30 - 5:20 Conference Sessions

Monday
June 23
4:30–5:20

 

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MDM and DG as a Business Tool for Data Standardization
Bibi Ephraim, Manager of Data Policy and Governance, Cisco Systems

Today, more than any other time in history, data driven business decision-making is one of the key ingredients for success. As organizations grow in size and complexity, standardization and consistency in usage and reliability of data is extremely critical. Inability to standardize and employ information consistently throughout an organization leads to significant inefficiencies, but, much more importantly to non-optimal business decisions. This presentation discusses data governance tools, processes, and implementation best practices that are uniquely developed and employed within Cisco Systems. The focus will be on the business drivers for leveraging data as key enterprise asset, the success factors and, the resultant outcomes.

Level of Audience
Intermediate

Speaker:
Bibi Ephraim Bibi Ephraim
Manager of Data Policy and Governance
Cisco Systems

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Monday
June 23
4:30–5:20

 

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Big Data Panacea! Big Hype?
Dennis Waldron, Senior Vice President, Chief Data Steward, Northern Trust Wealth Management

Information is the new currency for our millennium. Comprehending governed information from raw data will be the virtual power behind your business. Are you continually bombarded from vendors for magic-bullet Big Data solutions? Is that vendor “Marketecture” slide too good to be true? Is the quickly changing acronym vernacular adding confusion to your frustrated stakeholders? Are you concerned how to manage this information and make it of a quality consumable asset? This presentation will give pragmatic acumen for understanding the capabilities of the technologies, reasonable discernment for supporting your stakeholders who know just enough to be dangerous, and functional awareness of governing complex and high volume information.
  • Welcome to the future, the present, and now the past of your business…
  • Big Data? Give me the scoop on Hadoop?
  • Doctor, it hurts when I do this. (Don’t do that)
  • I’m too immature for governance?
  • Complexity Schmexity!
  • Batman’s utility belt for governance.

Level of Audience
Intermediate

Speaker:
Dennis Waldron Dennis Waldron
Senior Vice President, Chief Data Steward
Northern Trust Wealth Management

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Monday
June 23
4:30–5:20

 

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Data is the Product – An industrial manufacturer’s journey into Information Quality
Erin Clancy, Corporate Business Data Analyst, Fernco, Inc.

Increasingly data has become an essential component of industrial products. From the product descriptions, to product application data to regulatory data such as country of origin and raw material specifications, data is a raw material of industrial products.

Like any raw material, data quality must be managed. Applying techniques such as Lean and Six Sigma to data helps but is not itself a complete solution. Although data management techniques are available, adapting these techniques to an industrial manufacturing environment requires pragmatism.

In this session we will show how data management techniques such as the use of a metadata registry and taxonomies and ontologies were adapted to help improve data quality and the value of data. We will show how data profiling was used to expose the quality of the raw data and how ontologies were used to improve the sale-ability of products.

We will present the lessons we learned in the process of developing a data quality program that is comprehensive, sophisticated and pragmatic. How a data quality program can help improve major decisions such as the selection of an ERP system.

  • The design a data quality program
  • How to deploy data management techniques in an industrial manufacturer
  • Identifying ways to increase the value of data through quality
  • How to deploy sophisticated data quality in a pragmatic way
  • Challenges that remain

Level of Audience
Intermediate

Speaker:
Erin Clancy Erin Clancy
Corporate Business Data Analyst
Fernco, Inc.

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Monday
June 23
4:30–5:20

 

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Sold! Gaining Executive Buy-In for Data Governance
Anthony Algmin, Data Governance Practice Lead, West Monroe Partners

Data Governance professionals have a deep understanding of its value to organizations, but too often burgeoning governance efforts fall on deaf ears at higher levels, especially when looking for resources. This is not because data governance is a poor investment – it’s because we often fail to connect the activities to business impact in ways that executives demand. There are two reasons for this.

First, we have the terminology all wrong: “Data” Governance is not really possible – data makes no decisions of its own. Data Governance is actually about providing “people” with the context they need to make appropriate decisions – and data is where we measure the consequences of these decisions.

Second, Data Governance is not very tangible or intuitive. Too often we try to build a business case talking about the process and what we will do. Those are less meaningful than the outcomes we will drive, and how they will impact the business.

This session will highlight:
  • How a “typical” executive views Data Governance
  • Pivoting the focus from “Data” Governance to enabling people’s decision-making
  • Getting past the ROI question: quantifying is best, and what to do if you don’t have numbers
  • Marketing Data Governance: getting sign-off and resources is just the beginning

Level of Audience
Intermediate

Speaker:
Anthony Algmin Anthony Algmin
Data Governance Practice Lead
West Monroe Partners

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Monday
June 23
4:30–5:20

 

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Getting Shell's Product Life Cycle Management Data Process Healthy  
Tom Kunz, Downstream Data Manager, Royal Dutch Shell,

In 2009, the Product LIfe Cycle Data Management process was overweight, slow and lethargic. It took over 3 weeks to set up a new product and the Shell's Downstream businesses were clamoring for change. Three organizations (Fuels, Lubes, Data) banded together to deliver an 86% improvement in cycle time which resulted in millions of dollars in annual savings.
This presentation will track the steps of the journey including the frustrations, setbacks, failures and successes along the way.

It will address the following questions:

  1. What makes for a successful data program?
  2. When is the right time to tap into technology?
  3. How do you get the hearts and minds of leaders committed to improving data quality?

Level of Audience
Intermediate

Speaker:
Thomas Kunz Tom Kunz
Downstream Data Manager
Royal Dutch Shell

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Monday
June 23
4:30–5:20

 

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PANEL: Data Governance Challenges in Healthcare
Moderator:
Eileen Koski, Director, Data Governance, North Shore LIJ Health System
Panelists:
Curt McAdams, Manager of Data Modeling, Care Source
George Yuhasz, Director, Data Process & Governance, HealthNow New York Inc.
Laura Tellmann, Director, Clinical Informatics, BJC HealthCare

This panel of practitioners working in healthcare will discuss the challenges they are addressing in implementing data governance in their organizations.

Topics include:

  • How data governance in  healthcare is different than other industries
  • The impact of the Affordable Care Act
  • Handling new information sources
  • Big data and health care
  • Challenges of NPI (National Provider Identifier) and EMPI (Enterprise Master Patient Index)
  • Sharing of data with external organizations

Level of Audience
All levels

Moderator:
Eileen Koski Eileen Koski
Director, Data Governance
North Shore LIJ Health System

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Panelists:
Curt McAdams Curt McAdams
Manager of Data Modeling
Care Source

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  George Yuhasz George Yuhasz
Director, Data Process & Governance
HealthNow New York Inc.

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Laura Tellmann

Laura Tellmann
Director, Clinical Informatics
BJC HealthCare

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