Riding the Wave of AI

By: Katina Fischer CDMP, CIPM

When we look at the discipline of Data Management, most will quickly recognize that the core concepts surrounding governance are not new; they have been around for a very long time, going back decades, really. In fact, this very DAMA Portland Chapter started in 1985. While the technology around us changes at a pace that can certainly feel daunting at times, the fundamentals of data management are the same; it is the strategies or tools we use to implement them that have evolved. Now, over the years, many of us have experienced first-hand these changes and have been impacted by or seen the variety of ways in which each technological shift has helped forge forward the maturity of a given area within data management. But there is one change currently upon us that will certainly impact them all in one way or another. The rise of AI and how it is shaping the ways in which we collect and use data will fundamentally have the biggest impact we have seen in decades on the importance of data management and governance as a core organizational discipline. Data management is riding the wave of AI and with it, will usher in a renewed focus on each core concept; data quality, security, and governance just to name a few.

But why is it becoming so important now? There are many organizations jumping in on the opportunities AI presents, and many are attempting new projects with AI being a key element to gain new insights or efficiencies. However, as they are embarking on these new journeys some are quickly realizing they do not have a good enough handle on the fundamental core competencies of their data to even use AI in the way they had hoped. Many will need to take a step back to implement these fundamentals to truly reap the benefits of the new technologies and models surrounding and supporting AI initiatives. Every organization has its own unique strengths and opportunities, and with that, every organization is on a spectrum of maturity for data management. As we kick off this new year, it is a good time to take a step back and evaluate your organization’s strategies and maturity as it relates to data management and governance, which may, in turn, assist you in understanding your readiness for AI. And for those organizations taking a more cautious approach with regards to AI, a solid data management program will provide the organization the ability to implement a more secure and strategic approach to exploring or adopting AI related initiatives when it is ready to do so.

Maturity Assessment Levels

To perform a maturity assessment, working with your team(s), use the maturity assessment level guide below to identify your organization’s maturity level goal for a given data management capability as well as your current maturity level status. ¹

• Level 0: Absence of the capability
• Level 1: Initial or Ad-hoc: Success depends on the competencies of individuals
• Level 2: Repeatable: Minimum process discipline in place.
• Level 3: Defined: Standards are set and used.
• Level 4: Managed: Processes are quantified and controlled.
• Level 5: Optimized: Process improvement goals are quantified.

Plotting these metrics will help visualize the opportunities and aid in developing a roadmap to target initiatives to improve upon any capabilities that may be lagging. This process is also useful for plotting capabilities against a specific goal, such as AI initiatives, to determine what capabilities you will need to be proficient in to ensure success for a given project. Performing an annual assessment like this will assist in managing a continuous focus on the progressive growth of your data management program and the ability to tie these initiatives to your organization’s overall strategic objectives.

Upcoming DAMA Portland Events

The focus this year for our chapter is to continue to build a robust educational community around us, allowing us the opportunities to connect and share our experiences, learning from each other and riding these waves together. If AI is the wave our board is riding right now, then data management is the tether keeping it from getting away from us! Kicking us off in January we started with a session on Data Quality with Dan Myers from DQMatters. February will feature Data Governance by Design with Christina Burnett from T-Mobile. March will be our next in-person event, stay tuned for more details on that one and in April we will feature Data Strategies as Cornerstone if you want to use AI in Advanced Analytics by Marilu Lopez, CEO SEGDA.

We look forward to seeing you at our virtual and in-person events this year and hope you will continue to engage with us and share your knowledge and experiences as we grow in this field together.

Spring Conferences/Events

• Data Modeling Zone: March 4-6, 2025, Phoenix, AZ (DAMA-I Members receive a 20% discount)
• EDW and DGIQ: Combined into one conference this year. May 5-9, Anaheim, CA (Details)

1. For a more detailed description of the assessment levels and their characteristics refer to the DMBOK 2^nd Edition, Chapter 15, Data Management Maturity Assessment. ↩︎