Virtual Summit: Presentations

Getting in Front of Data Quality

Dr. Thomas C. Redman ‘The Data Doc’
Founder - Navesink Consulting

This fast-paced presentation crystallizes what it takes to improve data quality.

The unfortunate reality is most data quality efforts fail. But those who approach the opportunity properly, put the right people in place, and use proven methods, can produce great results, relatively quickly and easily.

This presentation covers:

1. Approach: Why eliminating the root causes of error is the only way to go.

2. What You Need to Do: Including understanding customer needs, measurement, control, and improvement.

3. Who Does the Work: An important first step involves getting responsibility for data out of IT. And everyone who touches data has a role to play!

4. Why: Bad data have always cost time and money. Lots of both. Today, as organizations seek to leverage big data and become data-driven, the costs are even greater. But subtle.

5. Culture: Every manager can improve data quality within his or her span of influence. Leadership is decisive.

Data Governance by Stealth: A Phased Approach to Data Governance

Presented by Chris Bradley

In this presentation, world-renowned information management expert, Chris Bradley, explores an alternative strategy for Data Governance.

Join Chris as he teaches how to ‘fly under the radar’, building your Data Governance capability in phases and aligning disparate centres of excellence to construct a robust framework and strategy for Data Governance.

Some of the topics include:

1. What is Data Governance – a simple definition

2. Why is Data Governance critical and what are the impacts of poor Data Governance?

3. Case studies of poor Data Governance

4. A framework and organisational models for Data Governance

5. Getting started in chunks and connecting islands of excellence

6. How to avoid Data Governance ‘knockout blows’

7. Bite-sized Data Governance: Summary

Master Data Management: Defining MDM Maturity with a Continuous Improvement Approach

Presented by Mark Allen

Common to any MDM strategy is the need to transition master data from an insufficiently managed state to a highly managed and controlled state necessary to achieve MDM goals.

Achieving MDM goals requires a well orchestrated plan and set of key milestones spanning various disciplines, practices, capabilities, and improvement areas. Capturing the essence of this as a high level, measurable program strategy is what a maturity model is for and why continuous improvement needs to be a key focus throughout the maturity process.

This presentation covers how to define an MDM maturity model, how to apply maturity measurement consistently across an MDM program, and provides examples of various maturity milestones that should be tracked. This presentation will also discuss reasons MDM maturity can hit a wall, what are maturity inhibitors, and how to maintain momentum through a well focused continuous improvement approach.

Top Data Governance Mistakes and How to Avoid Them

Presented by Nicola Askham - ‘The Data Governance Coach’

Data governance is getting a reputation for being complex and extremely challenging to implement, but it need not be.

Learn from others experiences and do not repeat their mistakes. Join Nicola Askham, The Data Governance Coach, to hear about the many pitfalls that you could face, how you can deal with them and more importantly avoid altogether if you take a structured approach to your data governance initiative.

Setting up a Data Quality Risk Management Program at your Organization

Presented by Alex Borek

Poor quality data often leads to major risks in all parts of an organization, affecting operational efficiency, bottom-line results, customer satisfaction and strategic decision making.

Monitoring, measuring, and quantifying how information quality impacts business objectives on an enterprise wide scale – both financially and non-financially, can become, however, a tricky task.

Using Lean Principles to Manage the Data Value Chain

Presented by Mario Faria

Creating and managing a data office is not an easy task.

The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.

Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.

This session will explore how it can be done.

Competing with High Quality Data – Building and Executing a Successful Data Quality Approach

Presented by Rajesh Jugulum

Because of the adverse impacts that poor quality data can have, organizations have begun to increase the focus on data quality in business in general and they are viewing data as critical assets like others such as people, capital, raw materials and facilities.

Since the data quality field is experiencing explosive growth, many companies have started to realize the importance of having a dedicated data quality (DQ) program to ensure that the data is fit for the intended purpose.

This presentation aims at outlining a holistic DQ approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices and ensure robust and reliable data is available to make judicious decisions.

The proposed DQ approach that is based on DAIC (Define, Assess, Improve and Control) project life cycle, is a structured, systematic, and disciplined approach to ensure that we are getting satisfactory levels of data by minimizing cost of low quality data. This in turn, strikes a balance between rigor and creativity resulting in reduced DQ assessment and issue resolution times.

The presentation also includes some case studies from large organizations.

Metadata Management as a Key Component to Data Governance, Data Stewardship, and Data Quality

by Dalton Cervo

For many organisations, their data landscape is one of disparate and fragmented silos, resulting in conflicting data. These conflicts cause considerable operational waste and severely limit the strategic performance of leaders.

The answer, of course, is to adopt modern attitudes and approaches to data management. However, many organisations fall into the trap of delivering disparate data management disciplines that fail to align, and so the problem repeats itself.

Metadata Management is a core method that needs to be aligned with every aspect of your Data Quality, Data Governance and Data Stewardship initiatives. In this presentation, globally recognised practitioner and author Dalton Cervo provides a detailed account of how to make this alignment a reality.

Little Data in a Big Data World

Presented by Laura Sebastian-Coleman

In this presentation, data quality expert and author, Laura Sebastian-Coleman explores the data quality challenges in healthcare and their impact on Big Data initiatives.

Topics include:

• The promise of Big Data in Healthcare

• Challenges with the quality of healthcare data

• Academy health examples

• Science, commerce and data quality implications

• Butterfly effect in data quality

• Making good on promise of healthcare data analytics

• Recognising and reducing variation in data quality

It’s What’s Inside That Counts: How Your People Can Lead Your Data Governance

Presented by Charles Joseph

In this presentation Charles Joseph provides an account of how specialist insurer, Beazley, is taking a people-centric approach to Data Governance.

Charles focuses on a range of key issues that companies need to address such as:

• Selling complex data governance and data quality initiatives to the business

• Engaging with supporters and evangelists to gain maximum traction

• Assigning roles for data governance

• Understanding the exact questions you need to address in order to be successful

Understanding Privacy Impact Assessments for Information Governance, Quality, Ethics and Success

Presented by Daragh O Brien
Managing Director of Castlebridge Associates

This session is about Privacy Impact Assessments, Ethics and Governance and how we can use or adapt existing tools and frameworks to help us address the new challenges such as GDPR that are emerging.

Daragh explores how modern architectures, such as Big Data Analytics, are impacting the privacy of consumers and regulatory directives.

Topics include:

1. What do we need to plan?

2. The curse of the mad data scientist

3. Examples of data quality trainwrecks

4. Privacy by design – the architecture required

5. Creating a plan for Privacy by Design and Privacy Engineering

6. Privacy Impact Assessments – what are they and where in the PMBOK life cycle?

7. The cost pyramid and the decision thresholds of a Privacy Impact Assessment

8. 6 step approach to Privacy Impact Assessments

9. Data Commissioner viewpoint of Privacy Impact Assessments

10. FMEA – Failure Mode Effects Analysis

Becoming a Data Driven Organisation: Aligning Business & Data Strategy

Presented by Donna Burbank and Nigel Turner

In this presentation, information management experts Donna Burbank and Nigel Turner, provide a deep-dive into the practicalities of creating a data strategy that perfectly aligns to your business goals.

Topics include:

• Components of a Data Strategy

• The DMBOK Framework

• Building an Enterprise Data Strategy

• The Interdependency of Business and Data Strategy

• Transforming the Business Through Data

• Creating a Business Motivation Model

• Case Studies: What Works in Real Life?

• Roles and Culture in a Data Strategy

How To Gain Business Buy-In for Data Governance

Presented by Nicola Askham - ‘The Data Governance Coach’

Over the past thirteen years or so, Nicola has learnt the right and wrong ways to go about gaining business buy-in for data governance.

In this presentation, she shares her best advice on the topic and shows how to articulate the benefits of data governance in a meaningful way.

Topics Include:

• What is Data Governance?

• Generic Benefits of Data Governance

• Translating Generic Benefits into Benefits that are relevant to your organisation

• Top Down or Bottom Up approach?

• Creating a Conceptual Data Model

Data Quality and the Impact on Decision-Making

Presented by Christoph Samitsch

This presentation explores the relationship between data quality and decision-making. Not only is there strong evidence that data quality influences decision-making performance, but the time it takes to make a decision may also be a variable affected by that.

Christoph shines a light on what constitutes data quality, including a focus on data quality dimensions as identified from past research efforts.

The presentation explores the decision-making process and how data quality comes into play when talking about an increase or decrease of decision-making performance. An example scenario for which this assumption could be applied is the usage of Decision Support Systems, which are often used in a professional manner or for personal purposes. As an example, Google Maps is heavily used by users as a spatial Decision Support System with the aim to make decisions more efficiently.

Finally, the presentation explores conducts research on the decision-making process and includes hypotheses the presenter has attempted to confirm. Christoph rounds this up with the main findings of his thesis and suggestions for future research.

Data Governance and Data Quality: A Keystone to a Successful Data Transformation Process and Strategy

Presented by Eric Callmann

In this presentation, Director of Data Operations and Strategy, Eric Callmann, walks the viewer through the Data Transformation Process of Platts and how Information Governance forms a central hub to the entire process.

Some of the topics include:

• Which data quality dimensions Platts are using to ensure high quality foreign exchange data

• How normalization helps extend the value of the data

• The key activities of information governance at Platts

• The end-to-end process of validations and checks that Platts use to ensure high quality throughout the data transformation process

Ethics in Information Governance

Presented by Katherine O'Keefe
Castlebridge Associates

In this presentation, Katherine O’Keefe discusses:

1. Ethics and their relevance to Information Management Practices

2. Developments in new technology and how that relates to human rights and privacy

3. A brief overview of ethical first principles

4. A framework for ethics in Information Management

5. An overview of practical methods to align ethics with Information Governance – looking at risk management and Information Management practices

Applying Data Quality and Confidence in The Environment Agency

Presented by Angie Wills and Rebecca Strickland | The Environment Agency

The Environment Agency is a public sector organisation and with increasing data transparency from public bodies, data quality is taking centre stage.

This session outlines our experience of using a pragmatic approach linking data quality and confidence to impact in our outcome focused organisation. We will discuss: How we worked internally to identify and prioritise data quality and the risks when data fails to meet our expectations How we linked data quality to outcomes in an organisation that isn’t revenue driven The data quality issues we faced The benefits we realised

Data Quality in Emerging Markets

Presented by Gary Allemann

Emerging markets such as those in Africa, South America and Asia present unique data quality challenges that frequently overwhelm Euro or US centric approaches and technologies.

These challenges include:

• High levels of illiteracy amongst both customers and staff

• Immature IT environments

• Lack of standards and variety from country to country

• Multilingual populations

• No fixed addresses (or no standards)

• and many more

These economies together represent almost 50% of the global population and present opportunities for growth that make them attractive to global businesses.

This presentation focuses on some of the unique challenges experienced in these environments by the speaker, and present strategies for dealing with these.

Welcome to the Data Zoo!

Presented by Julian Schwarzenbach
Director, DP Advantage

The behaviours of staff towards data can have a critical impact on the data used by an organisation. Sometimes users, with best intentions, do the craziest things with data. Our popular Data Zoo concept explores the ways that people interact with data, the good and bad points of these interactions and, most importantly, the organisational factors that influence data behaviours. The Data Zoo has been updated to reflect the latest thinking and also has had a visual make over and will form the basis of this presentation. Do you know where your Data Squirrels store their data? Do you know how to deal with Data Anarchists? Do you know why you should have a Data Evangelist?