The VA Data Strategy and Roadmap and the VA/DoD Joint Strategy Roadmap Milestone

Abstract Pending

View the presentation, The VA Data Strategy and Roadmap and the VA/DoD Joint Strategy Roadmap Milestone

Achieving Data Acumen: Improving Workforce Data Literacy (and therefore performance!)

More than half of work is accomplished by knowledge workers–usually defined as those who must “think for a living” [Davenport, 2005]. I contend that all knowledge workers work with data. Since most learn about data individually (if at all), the opportunity to gain from communal or best practices learning has not been present. Most refer to this as a lack of data literacy. Whether applied at the individual or organizational level, literacy is a binary concept and our data needs are more varied. Data proficiency and data acumen are more descriptive/useful terms and these should also be used to describe today’s organizational data knowledge requirements. This program will describe five specific data knowledge requirement levels and objective behaviors that must be demonstrated by those operating at each level. Lack of this data knowledge has so far hindered society from fully realizing our collective potential benefits. More importantly, organizations adopting these data knowledge requirements can directly and immediately improve organizational knowledge worker productivity. Delegates will:

  • Learn why the term data literacy is insufficient to describe the challenge and how the progression from literacy ➜ proficiency ➜ acumen is more operationally viable
  • Understand five data knowledge requirements levels in terms of their data leverage type, data skills type, ethical perspective and behavioral focus
  • Be able to match data knowledge requirements levels with types of organizational requirements
  • Begin to estimate the dollar ranges of potential knowledge worker productivity improvements in their organizations

View the presentation, Achieving Data Acumen: Improving Workforce Data Literacy (and therefore performance!)

How to get data management as part of data driven

Your organization has stated it is going to be data driven. Perhaps some mandate were handed down, or some data scientists are working in functional areas. But wait – why no formal data quality program? Or metadata? Or management of data movement and access ? Has anyone thought of data privacy? Too often there is a complete disconnect between lofty goals of leadership and practical solutions. The big issue is lack of awareness about what data driven really means, and the potential issues that can arise along the way. This presentation will cover:

  1. What essential elements are needed to present to management to demonstrate that “data driven” requires some sort of forma data program.
  2. How to craft a solution to the problem quickly when you are challenged.
  3. How to build a case to “step up,” and communicate risks to leadership

View the presentation, How to get data management to be part of your data driven organization

Assessing Data Quality in the Covid-19 Metrics. A Case Study.

There is often a long path between the reality which raw data describes, and decision-maker understanding of what is going on (“big picture”). This “data-to-understanding supply chain” has many steps, with potential for lapses in the quality of data and information. This gap (with threats to quality) is particularly evident in the flow of Covid-19 data being passed around units of government in the U.S. The state and county totals suffer from a variety of definitions, inconsistent processes, and various sources of delay in reporting. This slide presentation provides simple explanations of the kinds of tests (antigen vs. antibody), and other issues of false negatives, comorbidity, and sampling techniques. Ambiguities abound. We shall also consider other new metrics which would be useful to understand this pandemic. We shall also touch on best practices (or ineffective techniques) in data visualization with some excellent examples (of both) from government sources.

View the presentation, Assessing Data Quality in the Covid-19 Metrics. A Case Study.

Applying AI and Machine Learning to Data Quality and Privacy

Attendees will learn from real scenarios where AI was applied to Data Quality and Data Privacy to better govern an organization’s data. Poor data quality is costing companies and federal agencies millions of dollars due to the need for manual rework, compliance related fines, etc. as well as opportunity costs. We will walk though financial services and healthcare industry case studies to illustrate how Numbers Theory and Machine Learning can be leveraged to discover data quality rules autonomously.

View the presentation, Applying AI and Machine Learning to Data Quality and Privacy

AI Opportunities and Risks Talk & QA

Developments in machine learning, deep learning, and artificial intelligence are introducing a new age of “Smart cities” and “intelligent enterprises”. From self-driving cars to home automation, AI has the potential to be the most disruptive class of technologies during the next decade. In this talk, Dr. Malek Ben Salem will introduce the audience to the technologies behind Artificial Intelligence and the suite of capabilities that it allows. She will also cover various applications enabled by these capabilities and the risks associated with AI. In order to deploy AI broadly and limit any negative implications, we need to build trust between human and AI, by developing AI that is trustworthy, i.e. AI that is ethical, resilient, and explainable.

View the presentation, AI Opportunities and Risks Talk & QA

Federal Data Strategy

Todd Harbour and Kathy Rondon will discuss the new Data Management statutory requirement and the current activities of Congress and the Executive branch.

  • Data Management as a statutory requirement
    – Current activities in Congress and the Executive Branch
  • How will the shift in the Federal Government’s Data Management focus effect data management programs?
  • What are the timelines and how will this impact me?

View the presentation, Federal Data Strategy

Infonomics: The New Economics of Information

Increasingly, IT and business leaders talk about information as one of their most important assets. But few behave as if it is. Executives report to the board on the health of their workforce, their financials, their customers, and their partnerships, but rarely the health of their information assets. And corporations typically exhibit greater discipline in managing and accounting for their office furniture than their data. In this talk, Mr. Laney will share insights from his best-selling book, Infonomics, about how organizations can actually treat information as an actual enterprise asset. He will discuss why information both is and isn’t an asset and property, and what this means to organizations and data leaders such as chief data officers. And he will cover the issues of information ownership, rights, and privileges, along with alternative data challenges and opportunities, and his set of generally accepted information principles culled from other asset management disciplines. This presentation will be beneficial for those looking to help their organization move beyond the trite “data is an asset” or “data is the new oil” lip-service to actually begin acting that way. Participants will learn and have an opportunity to discuss:

  • How to monetize information assets in a wide variety of ways, including a number of real world examples
  • How to manage information as an actual asset by apply asset management principles and practices from other asset domains
  • How to measure information’s potential and realized value to help budget for and prove data management benefits
  • How classic microeconomic concepts can be applied to information for improved data architecture & management, and economic benefits

View the presentation, Infonomics: The New Economics of Information

Info Management Case Study

Many executives and business leaders could care less about the details of “Intelligent Information Management” or “Data Privacy” or “Information Governance” or “Records Management” or “Intelligent Capture” or “Process Improvement” or GDPR or or or… Yet those of us those who do understand these terms related to data and information, and the impact they have on our organizations, are very concerned about getting these messages across to those who control the budgets and make the big decisions. How are you getting the point across to people in YOUR organization? How are you “selling” it, and are people “buying” it? How do you get YOUR initiatives off the ground? Join us as we have a brainstorming discussion about:

  1. Overall strategies on how to talk about information and data management (and all that it encompasses)
  2. Language shifts for when you’re trying to educate and/or convince/persuade/influence
    1. Exec / C-Suite
    2. Team leaders
    3. Colleagues
    4. The “other side” – ideas coming from Biz or ideas coming from IT
  3. Top KSAs needed to influence discussions on Intelligent Information Management (KSA = Knowledge, Skills, Abilities)

We know that the answers to all these questions start with “it depends” – on the organizational structure, culture, personalities, audience, etc. Today we’ll share different ideas that might spark THE perfect solution for you and your situation. So let’s talk about how to talk about that elephant – and artfully avoid the steaming piles it does leave behind.

View the presentation, Information Management at its Finest: How Do You Address the Elephant in the Room when You Can’t Call It an Elephant?

An Approach to Data Quality & Information Management

A number of newsworthy trends are highlighting the growing recognition of risks of exposing individuals’ personal and private information. The numbers and sizes of data breaches are exploding along with emerging indignance over corporations using and selling what is believed to be personal or private information have motivated the creation of a growing inventory of global regulations address the need to secure and protect individuals’ personal and private data. In this talk we will discuss data sensitivity, concepts of information risk, along with trends and ideas for instituting data governance techniques to improve overall data protection while reducing the constraints presumed to be imposed by data policies.

View the presentation, Data Governance and Trends in Protecting Sensitive Data