Presented by Nigel Turner

Getting Data Quality right remains a key challenge for most organizations. As more companies strive to be data-driven, establishing and sustaining a high-quality data foundation of accurate, complete, and reliable data is now more important than ever. Despite this, poor Data Quality remains the norm rather than the exception in many companies.

Why do these problems persist? Data Quality technologies have improved immeasurably over recent years, and today there are few large organizations that do not have at least one dedicated Data Quality tool somewhere in their IT estate. But, of course, this is set against a backdrop where today’s Data Management challenges are becoming increasingly diverse and complex, as the volumes and varieties of data continue to grow. Meanwhile, poor Data Quality continues to negatively impact company revenues and profits, increases costs, and exposes an organization to legal, regulatory, and reputational risks.

So how can organizations best tackle this continuing battle with Data Quality? This webinar suggests that the key to success is to adopt a more strategic approach by aligning the Data Management disciplines of Data Quality, Data Architecture, and Data Governance to deliver better data.

This session will address:
• What is Data Quality and why does it matter?
• The business and societal impact of continuing poor Data Quality
• The inadequacies of traditional Data Quality approaches
• Strategic approaches to tackling Data Quality
• Creating and operating an aligned and unified Data Quality, Data Architecture, and Data Governance framework

Presented by Kelle O'Neal

You’ve operationalized Data Governance (DG), now what? Next-Generation Data Governance presents the next stage for educating and enabling DG professionals along their journey to evolve with and adapt to greater demand for agility, output, transparency, appropriate usage, and – for many — defensible data privacy compliance. Instructor Kelle O’Neal builds on the information and techniques of foundational governance to highlight critical areas and approaches for how organizations and operating models can evolve to meet current demand while leveraging new trends in focused tools and supporting technology to ensure adoption and continuing value.​

Presented by Robert S. Seiner

Metadata is essential to the success of Data Governance programs. Organizations’ first ventures into Metadata Management often revolve around the operations of data catalogs, data dictionaries, and business glossaries. These are the first tools used to drive the value of metadata into the business.

Spend the session with Bob Seiner, where he will discuss when and how to effectively use catalogs, dictionaries, and glossaries, how to govern this specific metadata, and what to consider for everything Metadata Governance. Metadata is a complimentary discipline to Data Governance. However, the metadata will not govern itself.

In this session Bob will discuss:
• What it means to govern metadata
• Metadata to include in catalogs, dictionaries, and glossaries
• The role of the metadata steward
• Governing the three levels of metadata
• Staying non-invasive in your approach to metadata

Please take a moment to stretch your legs, grab a beverage or snack, and come back at 11:30 am to hear our keynote presentation!

Presented by Nate Haskins

Data sits at the center of all S&P Global products, with information gathered from thousands of sources, cleansed and classified, with derivative works created and delivered in support of various workflows. Data collection, transformation, storage, and dissemination at this scale requires governance, and we at S&P Global believe in Data Governance in action. The word “governance” often conjures up images of dusty binders of documentation and layers of bureaucracy. Not at S&P Global. Here, Data Governance is anchored by a “middle tier,” a common descriptive layer that outlines, in a machine-readable format, an extensive set of metadata. Text documentation rarely delivers value that makes up for its production and maintenance cost. Documentation at S&P Global drives and accelerates the development process.

The keynote will cover the below points:
• Current Data Governance framework at S&P that enables us to handle data at scale
• How we are bolting modern technologies like Natural Language Processing, Machine Learning, and Robotics Process Automation into our Data Governance framework
• Democratizing low-code technologies and enabling our workforce to leverage and augment our data assets in a seamless manner
• How we are delivering and assessing the value to our customers and shareholders
• Our philosophy and commitment to Data Quality

Presented by Amirah Fayek

Peter Drucker was right when he wrote, “What gets measured gets managed.” Is your Data Governance program working? How do you know? Performance measurement is a critical component to successfully managing Data Governance and ensuring impact and effectiveness of your efforts. Whether you are struggling to determine impact, or demonstrate the value of the program across your organization, developing a measurement framework will help you tell your story. This presentation describes and demonstrates how to go about developing a useful performance framework and measure the maturity of your Data Governance program. See first-hand the evolution from a strategy document and roadmap to creation of a program logic model, measurement, and reporting.

Primary takeaways:
• How to move from a strategy to actual measurement
• Ideas on various measures and measurement techniques
• Program logic model example and reporting methods
• Approach to measuring program maturity

Presented by Anthony Algmin

It is often said that even if your organization has no formal Data Governance, you are still “governing” your data in some way. The same cannot be said for Data Leadership, as it is often entirely missing from our organizations.

Part of the reason we have traditionally struggled with Data Governance is that it represents only part of the data coordination our businesses need. Data Leadership complements traditional Data Governance, expanding its influence throughout the entire data lifecycle—transforming passive influence into data-driven momentum. Data Leadership is a growing topic in the Data Management community, and for good reason: it connects all of the data stakeholders in our organizations and aligns them to the goal of creating maximum Data Value.

This session introduces how for any organization to be successful with data, the outcomes driven by data must connect to meaningful business improvements—and why those changes must be measured. If your current data oversight efforts are not being quantitatively managed, then this talk is especially for you.

Key Learnings Include:
• What Data Value really is, and why creating it is the goal of everything we do with data
• How Data Leadership complements Data Governance
• Why balance is the real key to governing with Data Leadership
• How to immediately start making a quantified data impact in your organization