Pre-Conference Tutorials and Conference Sessions -
June 3, 2019

Monday
June 3
7:30–8:30
Registration and Continental Breakfast
8:30 - 11:45 MORNING TUTORIALS

Monday
June 3
8:30-11:45

 

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T1: The First 11 Steps to Starting a World-Class Enterprise Data Governance Program  
David Marco, President, EWSolutions

This tutorial presentation will instruct attendees on the first 11 tasks that your data governance program will need to accomplish. Organizations that properly complete these steps are well on their way to a successful data governance program.

Participants will leave the workshop with a collection of artifacts that can provide real world success. Usable, detailed templates and processes will be provided and examined, based on the real-world experiences in data governance and data quality with major organizations. Attendees will be able to customize these artifacts to suit their organization's needs and culture.

Learning Objectives will include:

  1. Create a data governance program charter
  2. Form the Data Governance Council
  3. Create Data Governance rules of order
  4. Assess the current (as-is) data management state
  5. Define future (to-be) data management state & Define and prioritize council activities
  6. Build a Subject Area Model
  7. Identify detailed business cases for data governance
  8. Identify appropriate data stewards (chief, business and technical) and custodians
  9. Form the business data stewards into teams – by subject area
  10. Develop the Data Governance Program Scope document
  11. Create standard documents and forms

Level of Audience
Introductory

Speaker:
David Marco David Marco
President
EWSolutions

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Monday
June 3
8:30-11:45

 

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T2: A Roadmap for Building a Successful Data Quality Program: How to Get Started, and How to Assess and Improve What You Have 
John Talburt, Professor, University of Arkansas at Little Rock

Accurate business reporting and data analytics can only be achieved using high-quality data. Yet many organizations either do not have a data quality program, or they just focus on standardizing source data. Having a complete, ongoing program to measure, monitor, and improve the quality of data is a competitive advantage for an organization in today’s data driven economy. This tutorial is primarily for participants starting a comprehensive data quality program or wanting to assess and improve the capabilities of an existing data quality program.

Participants will learn:

  • The seven fundamental principles of data quality
  • The four pillars of data quality management every data quality program must have them
  • How to measure data quality – How to define goals, data quality metrics, and prioritize opportunities
  • How to use data quality analysis tools and techniques
  • How to interpret data profiling results
  • How to make a business case (ROI) for data quality
  • Hands-on Exercises

Level of Audience
Introductory

Speaker:
John Talburt John Talburt
Professor
University of Arkansas at Little Rock

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Monday
June 3
8:30-11:45

 

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T3: Assessing Your Existing Data Governance Program
Robert S. Seiner, President/Publisher, KIK Consulting/TDAN.com

Your Data Governance is now a couple of years old. You engage your Data Stewards. You make good use of your Data Governance Council. And you demonstrate consistent value to your organization. Or do you? Is this the state of your Data Governance program? Have you climbed every mountain? Do you feel like you are running out of places to add value? Perhaps there are there aspects of the program that can be improved.

This tutorial with Bob Seiner will focus on how to assess your existing data governance program, articulate strengths and address specific opportunities to improve. Bob will share advanced data governance techniques used to expand the focus from the disciplines you already formally govern into disciplines such as information quality, data protection, metadata or master data management, or even the lauded Big Data discipline. The session will help you move from routine to progressive.

In this session you will learn:

  • Steps to assess an existing program
  • Measuring and focusing on results over time
  • Using existing roles to address new tasks
  • Expanding into new areas of discipline
  • Maintaining a progressive attitude and direction

Level of Audience
Intermediate

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

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Monday
June 3
8:30-11:45

 

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T4: Growing Your Data Governance Program: Progress vs. Meaningful Impact 
Kelle O’Neal, Founder and CEO, First San Francisco Partners

“What gets measured gets done.” Or does it?

One of the biggest challenges in standing up and sustaining a data governance program is determining the true impact the program has made to the organization. When it comes to quantifying data governance success, metrics can help you establish a baseline, track your progress against goals, align expectations and even defend change – or additional funding.

But while metrics are a good start, as they are necessary to ensure alignment, relevance and value of your data governance initiative, they are not enough to truly translate data value into business value. You MUST link progress metrics with impact metrics and align everything to key business goals.

In this tutorial, Kelle will provide tips and best practices for:

  • Understanding why metrics are important and how to create them
  • Looking at business challenges, and then creating the measurement to address business needs
  • Identifying a list of example metrics to consider (including progress metrics, impact metrics and KPIs)
  • Ensuring measurement is iterative (the more you know, the more you can adjust your metrics and measurements to be more precise or focus on different things to drive value)
  • Communicating effectively with stakeholders to maintain alignment and commitment
  • Implementing a measurement process focused on creating business value

Level of Audience
Intermediate

Speaker:
Kelle O’Neal Kelle O’Neal
Founder and CEO
First San Francisco Partners

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Monday
June 3
8:30-11:45

 

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T5: Designing Modern Data Governance for the Data-Driven Business 
Donna Burbank, Managing Director, Global Data Strategy, Ltd

Becoming a data-driven organization is a key focus for the future innovation plans of organizations across many industries and regions.  The drive for fast-paced innovation and emerging technologies trends like IoT, Big Data, advanced analytics, and more can seem at odds with data governance.  But modern data governance approaches can augment business value with faster time to market built upon a strong data foundation.  This workshop provides practical approaches based on experience from real-world implementations to help you define a modern data governance program to support your organization’s business initiatives. 

Topics include: 

  • Modern Data Governance for the Data-Driven Business – what’s different?
  • Aligning business drivers with data initiatives for “quick wins”
  • Organizing the “people factor” for cross-functional buy-in
  • Building the technical foundation & metadata management
  • Where to start: practical tips for defining an actionable roadmap for long-term success

Level of Audience
Intermediate

Speaker:
Donna Burbank Donna Burbank
Managing Director
Global Data Strategy, Ltd

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Monday
June 3
8:30-11:45

 

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T6: Successful Data Governance for Data Lakes
Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

Data Lakes are becoming increasingly common in enterprises, and they present a new level of challenges for Data Governance. Data Governance is essential for the success of a Data Lake but must overcome a number of challenges. For instance, many enterprises have to acquire a wide diversity of data that must be cataloged within the Data Lake and must protect private and confidential data. This tutorial describes the tasks that a Data Governance function must perform for a Data Lake, and the capabilities that Data Governance must develop to the requisite level of maturity. Particular attention is paid to Data Acquisition, Data Preparation (“Wrangling”) and the needs of analytical models. Technologies, such as the Data Catalog, that support these activities are reviewed.  The relationships that Data Governance must establish with a wide range of units are described including relationships with Legal, Procurement, Risk, Compliance, Privacy, IT Security, Data Scientists, Data Architecture, and more. Overall, Data Lakes are driving Data Governance to play a coordinating and harmonizing role, which can be considered as a new way of working for Data Governance.

Attendees will learn:

  • The fundamental architecture of a Data Lake, and the special data management needs it has that Data Governance must address
  • The tasks that Data Governance must perform to ensure a Data Lake is successful
  • How to develop the capabilities that Data Governance needs for its enhanced role in Data Lakes.
  • How to deal with technologies in the Data Lake, including the Data Catalog
  • How to deal with the many different functions that are involved in the Data Lake, and how Data Governance plays a leading role in ensuring the success of the Data Lake

Level of Audience
Intermediate

Speaker:
Malcolm Chisholm Malcolm Chisholm
Chief Innovation Officer
First San Francisco Partners

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arrow12:00 - 12:30 SPONSORED SESSIONS - DATA GOVERNANCE AND DATA QUALITY SOLUTIONS

Monday
June 3
12:00–12:30

 

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1:30 - 4:45 AFTERNOON TUTORIALS

Monday
June 3
1:30–4:45

 

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T7: Practical Steps for Overcoming Political Challenges in Data Governance
David Marco, President, EWSolutions

Data and information are critical assets of any organization, and should be considered as valuable a resource as buildings, employees and products. As a result, the study and implementation of Data Governance programs have become key initiatives for most large organizations.  For a company to be successful in this endeavor they must first defeat the greatest obstacle of any data governance program…POLITICS!!

This intensive session will teach you about the 6 types of “problem” people that Data Governance programs traditionally have to deal with:

  • Rulers of the Status Quo (RSQ): They have power and influence. Are not proponents of your program and may be actively opposed to it
  • PAs (Passive Aggressives): They will avoid your emails, phone calls and meetings
  • Snipers: They don’t have authority but they will “bad mouth” your project every chance they get
  • Zealots: They believe in data governance but are highly inflexible and cause more harm than good
  • Debbie Downer: The name says it all. The train she takes only stops at the winery!
  • Mouse King: He only wants to protect his little kingdom while hiding his mistakes

Most importantly the attendee will learn the 7 best practices for dealing with these problem people. These best practices will be presented in great detail with real-world examples provided for each of the best practices.

Level of Audience
Intermediate

Speaker:
David Marco David Marco
President
EWSolutions

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Monday
June 3
1:30–4:45

 

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T8: Digging Deeper into Data Quality Management: Standards, Metrics, and Controls
John Talburt, Professor, University of Arkansas at Little Rock

There is always room for improvement and data quality management programs are no exception. This seminar is aimed at participants already engaged in data quality and would like to learn more about some of the more advanced techniques for assessing, monitoring, and improving data quality.

The tutorial will cover:

  • Developing a data quality management gap analysis using the ISO 8000-61 Data quality management reference model
  • How to design both objective and subjective quality metrics to drive data quality assessment and improvement
  • How to develop and write data quality standards and procedures to support a data governance policy on data quality
  • The Lindsey Three-Dimensional Analysis technique for data quality assessment
  • Developing and managing template-based data quality rules
  • Acceptance Sampling and Statistical Process Control for developing and implementing a data quality control strategy
  • Measuring precision and recall to assess data quality for master data management and data integration systems
  • Leveraging a centralized data quality issue reporting system for remediation and continual improvement
  • Data quality for Big Data and the Data Lake
  • Data quality, machine learning, and active learning

Level of Audience
Advanced

Speaker:
John Talburt John Talburt
Professor
University of Arkansas at Little Rock

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Monday
June 3
1:30–4:45

 

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T9: Managing the Changes  - How to Make your Data Governance Program Sustainable 
John Ladley, Principal, Sonrai Solutions

Data governance equals change, and managing change is the number one obstacle to Data Governance success. Managing change is required for a sustainable program, so the changes associated with data governance need to be identified, and the organization needs to be carefully led from current state to future state.

Too many data governance and information management programs end up as “shelf-ware”. This is expensive and disheartening. Simply put, Data Governance will not succeed without managing the changes and leveraging your culture.

It seems it is more difficult than it should be. Any group working to make data governance sustainable needs to understand why this is hard, ad what needs to be done.

This tutorial is specifically aimed at sustaining EIM programs, especially data governance. This includes an organization change management effort unique to data governance, data quality and other programs. This class will cover in detail the barriers to overcome and sustain the many efforts and initiatives required for successful EIM.

Attendees will leave with a basic tool kit for organization change management for DG.

This tutorial will cover:
  • The fundamental concepts of organizational change
  • Why the changes from DG cause issues
  • Prescribe activities to deal with obstacles and issues
  • How to plan for managing the change in your organization
  • How to build and manage the change team, from sponsors to stakeholders

Level of Audience
Intermediate

Speaker:
John Ladley John Ladley
Principal
Sonrai Solutions

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Monday
June 3
1:30–4:45

 

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T10: Catalogs, Glossaries and Dictionaries - Governing the Metadata
Robert S. Seiner, President/Publisher, KIK Consulting/TDAN.com

Organizations are implementing glossaries, dictionaries and data catalogs for numerous reasons. The delivery of these forms of data asset documentation requires governance of the information collected therein. The governance must be focused on the definition, production and use of this metadata.

Join Bob Seiner to understand the actions necessary to build and sustain successful glossaries, dictionaries and catalogs that improve the understanding of data, quality of data and protection of sensitive data. Bob will share best practices that lead to value received by these organizations.

In this tutorial, Bob will discuss:

  • The business case for glossaries, dictionaries and data catalogs
  • Actions taken to address these resources
  • Three levels of metadata to include in your metadata planning
  • What it means to govern metadata
  • Policies and procedures associated with metadata governance

Level of Audience
Intermediate

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

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Monday
June 3
1:30–4:45

 

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T11: A Review of Data Governance Tools
Sunil Soares, Founder & Managing Partner, Information Asset

This tutorial will cover data governance tools for the following requirements:
  • Business Glossary
  • Data Lake Governance including data ingestion, data quality, lineage and data masking
  • Operating Model for Stewardship
  • Workflows
  • Metadata Management
  • Reference Data Management
  • Data Quality Management
  • Alignment with Information Security and Privacy
  • Data Sharing Agreements
  • Integrations between different tools such as Data Governance & Data Quality, Data Governance & Hadoop
  • Overview of offerings from vendors such as ASG, Cloudera, Collibra, Hortonworks Atlas, IBM, Informatica, Oracle, Podium and SAS

Level of Audience
Advanced

Speaker:
Sunil Soares Sunil Soares
Founder & Managing Partner
Information Asset

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Monday
June 3
1:30–4:45

 

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T12: Implementing Agile Data Governance
Tami Flowers, Director, Governance Solutions, MetaGovernance Solutions, LLC
Once Data Governance has become a priority for your organization, how can you make it operational within existing Agile projects? Bringing together data, information, reporting, reconciliations, controls and stewardship into a platform to provide "one version of the truth" for an organization is not a small, or quick task. In this session we will discuss the key components of establishing a Data Governance Framework and expand into how to make it operational within Agile projects. Using Agile methodology for Data Governance focuses on deliverables that are valuable to the business and enable an organization to continuously build out an integrated data governance program that delivers accurate and timely information for operational or financial disclosure needs.

This will be an interactive session and we will use real examples so you can leave with ideas and knowledge that you can immediately use.

We will cover:

  • Components of Data Governance Framework and Agile, and how to use them together
  • Breaking down governance within existing projects
  • How to identify and write data governance stories
  • Integrating data governance into Agile ceremonies and artifacts
  • Tips and lessons learned to make Agile and data governance sustainable even in highly regulated organizations

Level of Audience
Intermediate

Speaker:
Tami Flowers Tami Flowers
Director, Governance Solutions
MetaGovernance Solutions, LLC

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Arrow5:00 - 5:45 Conference Sessions

Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - N0N-PROFIT
Improving our Data Driven Culture to Strengthen the Lives of Children and Families
Autumn McCants, Data Governance Manager, Starfish Family Services
David A. Williams, Chief Administrative Officer, Starfish Family Services

Starfish Family Services is a private, nonprofit human service organization, recognized as a champion for under-served children and families in metropolitan Detroit.  With over 500 employees, we provide high-quality programs and support services across 19 sites, with a focus on early childhood development mental wellness and empowering families. Starfish also has a reputation for operational excellence, with a focus on measuring outcomes in a data driven and evaluative culture. This presentation is a case study on how Starfish is implementing a large-scale data governance program and the skills needed to manage change and shift culture.

This presentation will cover:

  • Strategies for obtaining buy-in for data governance across different levels of the organization.
  • Our ‘kind-shepherding approach’ to data governance and data quality and how these soft skills have been vital to shifting the culture.
  • The different technical artifacts used like business glossary, data models, data warehouse and MDM foundation and how they helped both technical and non-technical staff understand their business needs.
  • The role integrating these technical components in daily work of business data owners, data stewards and data custodians played in shifting the culture.
  • Lessons learned: alignment of implementation pace with organizational readiness to embrace a robust data governance structure.

Level of Audience
Introductory

Speakers:
Autumn McCants Autumn McCants
Data Governance Manager
Starfish Family Services

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  David Williams David A. Williams
Chief Administrative Officer
Starfish Family Services

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Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - HEALTH CARE
Expanding Data Governance from a Data Warehouse Function to an Advocate of Core Values Across an Enterprise
Yolanda Griffin, Sr. Data Governance Analyst, Blue Cross and Blue Shield of Louisiana
Brian Badinger, Director, Enterprise Data Management, Blue Cross and Blue Shield of Louisiana

The mission of Blue Cross and Blue Shield of Louisiana (BCBSLA) is to improve the lives of Louisianans by providing health guidance and affordable access to quality care.  The inception of Data Governance at BCBSLA was initiated as a result of the Enterprise Data Warehouse implementation.  As the company goals matured to incorporate new strategies, the Data Governance Office was commissioned to expand its scope in assisting with delivery of the core foundational capabilities necessary to achieve BCBSLA’s mission.  Our focus on Data Stewardship, Data Management, and Partnerships allowed us to manage the integrity and security of enterprise data.  As a result, this enabled predicative analytics which supported provider care and preventative care management initiatives.  Session highlights include transformation activities and life-cycle phases for maturity:

Topics include:

  • Data Governance Mission:
    • Ease of data accessibility
    • Data source knowledge
    • Confidence in decision based on data integrity
  • Data Stewardship – Advocate for data steward community promoting awareness to the following capabilities:
    • Data Ownership
    • Accountability
    • Organization
    • Transparency
  • · Data Management - Provide centralized data extract management to improve data quality, reduce duplicated data feeds, and enable consumption from a single source of truth.
  • · Partnerships – Enterprise-wide focus on divisional alignment to company vision.

Level of Audience
Introductory

Speakers:
Yolanda Griffin Yolanda Griffin
Sr. Data Governance Analyst
Blue Cross and
Blue Shield of Louisiana

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  Brian Badinger Brian Badinger
Director, Enterprise Data Management
Blue Cross and
Blue Shield of Louisiana

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Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - PUBLIC SECTOR
Implementing Data Stewardship at the Bureau of Safety and Environmental Enforcement
Julie Conklin, Sr. Data Management Analyst, Bureau of Safety and Environmental Enforcement

The Bureau of Safety and Environmental Enforcement (BSEE) is spending over $20 million dollars a year collecting and storing information. This data is compiled in many different ways and with varying standards. Some of this data is used once for reporting and stored in multiple databases which make it difficult to share or to aggregate in order to understand regional or national conditions or trends. The Bureau's first Data Stewards are working to improve how data is collected, stored, and used so it can meet its responsibilities to inventory and report on the condition of public land. With the support of the Director and Department, BSEE implemented its first Data Stewardship Strategic Plan, Data Stewardship Team, and Data Stewardship Council.

So far, the team has been working to:

  • Develop, implement and improve standardized definitions of data elements and concepts.
  • Promote clear understanding of roles and responsibilities with respect to organization-wide data administration, data quality, data management processes.
  • Facilitate a consistent and unified understanding of relevant information and improvement of data quality.
  • Install business analytics to support error finding and decisions making within the bureau.
  • Support the Department of Interior's Open Data Initiative and the Federal Website, Data.gov

Level of Audience
Introductory

Speaker:
Julie Conklin Julie Conklin
Sr. Data Management Analyst
Bureau of Safety and Environmental Enforcement

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Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - FINANCIAL SERVICES
How is Data Risk Planned for and Operationalized Across a Data Governance Program
Stephanie Grimes, Sr. Tech Lead, Freddie Mac
Zainab Asif, Risk and Controls Manager, Freddie Mac

As data governance programs are established, a foundational aspect that needs to be considered and strengthened is data risk management and its implications. In this session, we will provide an overview of how a data risk strategy was implemented to address the inherent risk of doing business within a financial institution.

What you will learn:

  • The importance of a risk and controls strategy for managing data
  • Types of data risk (integrity, availability and confidentiality)
  • Whose responsibility is data risk management? Data Risk Roles and Responsibilities
  • Industry best practices for risk management (NIST, COBIT, COSO risk frameworks)
  • Data risk management at enterprise vs. department-level
  • Controls framework and implementation (including testing and audit functions)
  • Non-functional requirements for security, privacy and protection
  • Lessons learned and continuous improvement

Level of Audience
Intermediate

Speakers:
Stephanie Grimes Stephanie Grimes
Sr. Tech Lead
Freddie Mac

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  Zainab Asif Zainab Asif
Risk and Controls Manager
Freddie Mac

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Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - INSURANCE
Data Quality Through Business Model Templates
Venkata Komaragiri, Technology Manager, State Farm
Kevin Knipmeyer, Technology Manager, State Farm

This presentation will discuss the success of improved data quality through capturing the variations of chronological business scenarios on relational data. We will describe how we took an existing problem of unknown coverage for complex business processes to create test data and identified a designed solution to automate both test data and data quality checks for data transformation. We will show how it impacted our ability to deliver quality products, to provide complex transforms and move data to a new platform on an ongoing basis, with a much higher degree of confidence at a lower cost.

Level of Audience
Intermediate

Speakers:
Venkata Komaragiri Venkata Komaragiri
Technology Manager
State Farm

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  Kevin Knipmeyer Kevin Knipmeyer
Technology Manager
State Farm

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Monday
June 3
5:00–5:45

 

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Industry Special Interest Group - RETAIL
Transforming Siloed Teams into a Collaborative Powerhouse
Aida Biberic, Data Governance Analyst, Columbia Sportswear Company
Jennifer Canney, Enterprise Data Architect, Columbia Sportswear Company

When teams don’t share what they’re working on, groups with similar goals can end up misrepresented, communicating the same message with the same partners, or conveying a slightly different message that is ultimately trying to say the same thing. We have worked diligently over the past two years to ensure that our Data Governance, Information Security, and Enterprise Architecture teams are in sync, proliferating a united message, and working together to accomplish our goals.

Our relationships started out of necessity and have since matured into a functioning, proactive, collaborative powerhouse. We want to share our big “How’s”: how we started, how we’ve grown, how we share, and how we raise awareness for one another.

Topics include:

  • Roles and responsibilities of each team
  • Where overlap exists & how we operate
  • Challenges, issues, how we come to agreement
  • Continual learning and training 

Level of Audience
Intermediate

Speakers:
Aida Biberic Aida Biberic
Data Governance Analyst
Columbia Sportswear Company

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  Jennifer Canney Jennifer Canney
Enterprise Data Architect
Columbia Sportswear Company

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