Conference Sessions
November 19, 2013

Tuesday
November 19
7:30–8:20

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Level of Audience:
All Levels

Tuesday
November 19
8:30–9:30

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Yet often, disruptive technologies are the ones we never realized we wanted but become the things we need to have, such as the fax machine, the cell phone, the iPad, or the iPod. In this talk we will explore how to package data governance exactly the same way: we will look at the common denominators of these innovations, differentiating between the perception of what you get from each item from the item itself, presenting the story the right way, and how the same techniques can be applied to turn data governance into something that is amazing, extraordinary, and is something your organization can’t do without.

Level of Audience:
All Levels

Tuesday
November 19
9:35- 10:05

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Changing business strategies may divert the attention of key stakeholders and, by extension, the practitioners you depend on.  Perhaps you made the case and proved the value but initial processes aren’t robust or nimble enough to support a broader audience?  Or, since the project was finite governance was assumed to be finite also.

In this presentation, SAS Best Practices will unveil the key reasons data governance initiatives fail to thrive after the initial honeymoon period.   We’ll present the mechanisms best-practice companies enlist to ensure data governance remains strategic and relevant.  As well as key considerations for creating nimble, agile processes that enlist ongoing engagement from key stakeholders in both the business and IT.

Level of Audience:
All Levels

Tuesday
November 19
10:30–11:20

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In this session, we will discuss ways to overcome the following obstacles to successfully implement master data governance processes:

• Decision makers do not feel the pain.  They have staff spending hours working to align un-mastered data, of which they only see the results.  How can you get their buy-in to fix something they do not perceive as broken?

• Not my problem.  People supporting source systems operate within their silo, unaware of a need for enterprise wide consistency.  How can you get on their priority list if they do not perceive any problem with their current arrangement?

• Emotional attachment.  You will have to face people who have put in so much time and effort to design a system that works for a single function; they have developed an emotional attachment.  Changes to their developed processes can be perceived as a personal attack.  How can you overcome their perception to ensure the full cooperation needed?

• Been there - done that.  Some stakeholders have been around long enough to have seen failed attempts to implement master data governance in the past.  How can you triumph over their preconceived notion and convince them this time it will work and have lasting benefits?

Level of Audience:
Introductory

Tuesday
November 19
10:30–11:20

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This session makes the argument that it is time to recognize the “Data Steward Career” – and work to institutionalize it within these organizations and companies. Human Resources and senior management should have the role clearly articulated in the organization’s list of jobs, as well as a designated pay scale and career path. 

We’ll discuss an organization that formalized the role as a full-time position, one in which the role served as a path to the Management Track. Using that organization as a template, this session will discuss the following:

• Career Levels (Data Steward, Master Data Steward, Chief Data Officer)
• Roles and responsibilities of each
• Demonstration of skills and traits such as
  • Manage projects, delivering on time and within budget
  • Manage and motivate others
  • Work with individuals across all levels of the enterprise – from operational staff to mid-level managers to senior and C-level management
  • Exhibit presentation, communication and persuasion skills
  • Demonstrate data analysis, data security, data profiling expertise

We will also discuss steps that the Data Governance community should be taking in order to promote and establish its position within an organization. This includes the following:

• Identifying Director and VP-level advocates (Security, Compliance, Legal, etc.)
• Working with Human Resources to define the skills and establish a Data Stewardship career
• Tracking the growth of University-level coursework in Data Governance
• Templates for creating the job description, skills sets and responsibilities

Level of Audience:
Intermediate

Tuesday
November 19
10:30–11:20

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If your metric is Data Quality of a data element, you must first explicitly define the element means, what standards apply, what outcomes define quality, and what do you do if quality issues are found.

This presentation takes a Data Governance perspective on Data Quality by defining how the business needs to define and proactively manage its data quality initiative.

Topics covered include:

• Defining the differences between Policies, Standards, and Controls,
• Defining the roles of Business Sponsors, Data Owners, Data Stewards, and IT in the DQ process,
• Defining a Target vs. Actual data quality levels based on data value and business importance,
• Where an EDQ initiative fits in the IT infrastructure and business processes

Level of Audience:
Intermediate

Tuesday
November 19
11:30–12:00

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Level of Audience:
All Levels

Tuesday
November 19
11:30–12:00

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Visualization and mining algorithms can provide tremendous insights in data, and business users can use those to take the right actions and make the right decisions. New functions (e.g., data scientists) and skills (e.g., Hadoop) are essential, but they are also hard to come by.  It can be a big disappointment to learn that the data scientists can't figure out what "Customer" means, where that data can be found or shared from, or even who is responsible for it.

So how can you make sure that analytics move from a niche experiment to a structural, competitive differentiator?

In this session we will show how Data Governance and Data Stewardship provide the right level of control and trust in data. Data Stewards are the data worker bees to achieve this operationally: managing the business glossary, curating reference data, handling classifications, taxonomies and hierarchies, setting up policies and rules, measuring compliance, monitoring quality and resolving issues, facilitating data sharing, ... They enable the process of data management.

We will make use of Collibra's Data Governance Center to show how this works in practice, and how a configurable operating model (roles, workflow, organization, ...) drives the right level of adoption and business engagement to establish a sound approach to data maturity, and turn information into a competitive differentiator.

Level of Audience:
All Levels

Tuesday
November 19
1:00–1:50

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 Implementing a Master Data Management (MDM) solution is a journey and Data Governance is an important enabler for a MDM program’s success.  While data governance can often be an academic discussion, this session will focus on both practical and realistic approaches to Data Governance that you can emulate for success within your own organization. 

Key items that will be discussed are:

• Lessons learned, what worked and what didn't
• Best Practices to data governance
• MDM considerations for data stewardship
• Key success factors and metrics

The approach discussed during this presentation has been time tested over several successful projects at Citrix.

Level of Audience:
Intermediate

Tuesday
November 19
1:00–1:50

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At last year’s Data Governance Winter Conference we described how every data subject area must have a Governor that is accountable and a Steward that is responsible for its health and completeness.The initial round of metrics that described each subject area have been based on Data Completeness, Accuracy & Timeliness.These KPIs are aligned specifically to organizational cost, risk and revenue opportunities.

This year our session will focus on the progress we have made as the information hub and analytical repositories mature to support strategic initiatives, the development of more detailed metrics and enforcement of policies.One of the first steps in this roadmap is engaging  and empowering the Data Stewards with greater oversight and accountabilities to enforce policies of appropriate data use as described by the consensus activities recorded and published earlier in the information lifecycle.

Level of Audience:
Advanced

Tuesday
November 19
1:00–1:50

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Here are some of the topics to be discussed in this session:

• A reference architecture for Data Governance software
• Evaluation criteria to select Data Governance software tools
• The role of structured versus unstructured data governance tool
• The role of tools for Big Data Governance including Hadoop, NoSQL, In-Memory and Streaming
• The integration between different components such as the business glossary, policy management, master data management and reference data management

Level of Audience:
Intermediate

Tuesday
November 19
2:00–2:50

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Level of Audience:
Advanced

Tuesday
November 19
2:00–2:50

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Topics to be covered include:

• Facilitating the DG Council and maintaining business participation - The good, the bad, and the ugly!
  • Criteria for data steward selection
  • Roles and responsibilities of data stewards
• Perpetual training and mentoring of data stewards
• Promoting the DG strategic, corporate vision through project level involvement
• Data issue reconciliation – herding the cats!
• Data standardization – building group consensus
• Assisting business areas in documenting business value
• DQ Dashboard review – how to engage the business in root cause analysis and error remediation

Level of Audience:
Introductory

Tuesday
November 19
2:00–2:50

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Level of Audience:
Advanced

Tuesday
November 19
3:00–3:30

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This session will highlight some of the ways to:

• Show executives and line of business owners the connection between data quality and business goals and objectives
• Use metrics to demonstrate business value and return on investment

Level of Audience:
All Levels

Tuesday
November 19
3:00–3:30

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What You Will Learn:

• Scope of governance responsibilities, organization structures, and processes for consideration
• How to identify issues and tune your governance initiative to your unique culture and organization
• How to develop an iterative data governance implementation plan that enables phased growth

Level of Audience:
All Levels

Tuesday
November 19
3:40–4:20

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• Impact of dealing with sharing of data with other organizations
• The unique challenges to health plans in data governance
• Dealing with increased regulations
• Impact of new and changing lines of business to governance programs
• Data quality challenges in health plans

Level of Audience
Intermediate

Tuesday
November 19
3:40–4:20

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This session is targeted at employees of Medical Device companies who are wrestling with the most efficient way to create a unique identifier and proactively manage the quality and movement of their data.

During the session we will review:

• The FDA legislation and the impact it will have on your organization
• Current UDI data challenges and benefits
• How Data Governance and Enterprise Information Management support UDI
• How to get a UDI program started
• How to ensure a successful UDI program

Level of Audience:
Intermediate

Tuesday
November 19
3:40–4:20

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Key concepts include:

• Change Management Techniques, including demonstrating value to create Buy In
• Treating Data as an Asset
• Governance Boards and Policies that Make Sense for Federal Agencies
• Data Stewardship in a siloed environment
• Integrating Data Governance with IT Systems Development

Level of Audience:
Introductory

Tuesday
November 19
4:40–5:20

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Level of Audience:
All Levels