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Speaker Marilu Lopez, SEGDA

Marilu is the owner and data management consultant at SEGDA, specializing in data strategies and operating models. She co-founded and served as president of the DAMA Mexico Chapter, was the DAMA Regional Coordinator for Latin America, Presidents' Council Chairperson, and is currently DAMA Chapter Services VP. With a background of 30+ years in the financial sector, including 15 years in data management, Marilu holds a CDMP (Certified Data Management Professional) Master and CIMP certifications in Data Governance and Data Quality and is TOGAF-certified. She is the author of “Data Strategies for Data Governance” and an active speaker at international conferences like EDW, DGIQ, and DMZ.

Abstract Data Strategies are the cornerstone for driving AI in advanced analytics. Using a pragmatic, agile, and communicative (PAC) approach, organizations can anchor their Data Management priorities with a maturity model, then clearly define and communicate their strategic path forward using a concise strategy canvas.

Session Synopsis

A Pragmatic, Agile, and Communicative approach to defining the What, Who, and When of Data Management to have good data for AI.

Most organizations are living an urgency to get value out of their data. They are jumping directly to implement MDM initiatives, to move to the cloud, or to implement advanced analytics, and now, to adopt AI, without a real understanding of the problems that need to be solved and the priority to tackle them. There's though an increasing awareness of having to manage data in a better way, but there's no clear understanding of the path to follow. Data Strategy is the key element to prioritize and guide resource allocation in the best way. This session presents how to produce Data Strategies using the PAC (Pragmatic, Agile, and Communicable) (Pragmatic, Agile, and Communicable) Data Strategy Method.

Attendees will take away:

The relevance of a Data Management Maturity Model as an anchor for a Data Strategy The power of a Canvas to communicate Data Strategy The Data Strategies Framework The attainability of the Data Strategy PAC Method

Define your Data Strategies with the appropriate stakeholders in a very pragmatic and agile way and communicate them with the power of a Canvas.

Session Synopsis

AI Governance involves managing the trade-offs between innovation and risk management for artificial intelligence. This session will cover the following topics based on Sunil Soares’ books on AI Governance:

Agentic AI Governance – Best practices to implement governance within the context of Human-out-of-the-Loop.

People – Emerging roles and groups, such as the AI executive sponsor, AI governance leader, AI oversight board, AI steward, and AI center of excellence.

Process – 13 components and 100+ controls for AI governance.

Technology – Reference architecture to support AI governance including tools and vendors.

Regulations – Mappings of controls to regulations such as the EU AI Act.

Industry Standards – Mappings of controls to industry standards such as the NIST AI Risk Management Framework, OWASP Top 10 LLM and MITRE ATLAS.

Sunil Soares, Private Equity Exit/IAPP AIGP

Speaker Bio

Sunil Soares is the Founder and CEO of YDC, focused on AI Governance. Prior to this role, Sunil was the Founder and CEO of Information Asset, a data management firm, which he sold to private equity.

Sunil is the author of 12 books on data management and AI governance, including The IBM Data Governance Unified Process, Selling Information Governance to the Business, Big Data Governance, Data Governance Tools, Data Governance Guide for BCBS 239 and DFAST Compliance, The Chief Data Officer Handbook for Data Governance, and AI Governance. In the past, Sunil also worked as an auditor at PwC and as a management consultant at Booz and Company. Sunil was a member of the Institute of Chartered Accountants of India and has an MBA in Finance from the University of Chicago Booth School of Business. Sunil also holds the Artificial Intelligence Governance Practitioner (AIGP) certification from the International Association of Privacy Professionals. He has also successfully completed the IEEE CertifAIedTM Assessor Training for AI ethics assessments.

Speaker

Christina Burnett, T-Mobile

Christina has over thirty years of experience in consulting, data modeling, software integration, analysis, and programming. She came to Data Governance late in her career, but having a data-centric view of software has been a common thread throughout her work. Her software development background has given her a practical perspective on how to work with software development teams to improve Data Governance outcomes. Christina has a B.S. in Computer Science from the University of Houston, and an M.S. in Computer Science and Software Engineering from the University of Washington Bothell. Christina is certified as a Collibra Expert Level 2.

Abstract

We have shifted our focus from governing data when an initiative is complete, to beginning data governance during the design phase of the software development lifecycle. We walk with our development teams to ensure that governance is baked into the plan, not an afterthought. We determine the level of governance that is needed for new data products during design. This ensures that the development teams are not surprised by our governance requirements, reducing remediation, and improving the quality of the data products from their inception.

This presentation will include:

An explanation of the Governance by Design framework Demonstrations of workflows in Collibra to support the process Change management for both the Data Governance team and the other impacted groups RSVP required for entry ticket. This is a VIRTUAL event