Strategic data management is becoming increasingly critical as organizations navigate the complexities of today’s technological advancements.

With the integration of AI technologies emerging as a pivotal factor for success, businesses are urged to adopt a strategic approach that focuses on solving specific problems with targeted data. Emphasizing incremental improvements and strong governance, this approach ensures continuous value delivery, according to Tom Godden (pictured), enterprise strategist and CxO advisor at Amazon Web Services Inc. The need for clearly defined roles in AI and data management is also crucial to balancing innovation with practical implementation, driving businesses toward sustained success in a data-driven world.

AWS’ Tom Godden talks to theCUBE about strategic data management.

“I’m seeing the customers be more successful that have a good governance program, that have good control over their data so they can enter into effective IP sharing types of agreements,” Godden said. “But, again, it comes back to you need a good governance program in place.”

Godden spoke with theCUBE Research’s Dave Vellante and Sanjeev Mohan at the CDOIQ Symposium, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how organizations must adopt strategic data management and integrate AI technologies to solve business problems to ensure strong governance and drive continuous value.

Focusing on business-driven data solutions using strategic data management

It is important to take a business-driven approach to  data management, according to Godden. Rather than attempting to consolidate all data at once — a costly and often unproductive endeavor — organizations should identify specific business problems and gather only the data necessary to solve these issues.

“A strong governance program is part of that, automating the flow of your data so I have better control over my data and beginning to establish that data lineage, that data versioning, that data library, that catalog that you have for data,” he said. “Do I need to solve the inconsistencies between this data and this data? Not necessarily, unless the use case I’m working on requires me to resolve that inconsistency and then do it then to solve that business problem.”

Common pitfalls many companies face, such as the tendency to spend exorbitant amounts on comprehensive data organization without immediate benefits are also of concern. Instead, the focus should be on iterative improvements, addressing one business problem at a time and progressively building a well-managed data environment.

“Everyone is rushing to get to that data, but part of the struggle you mentioned is the data is siloed,” Godden said. “The data may not be as well organized and managed and controlled. The problem that I see lots of them doing is saying, ‘Oh, I need to pause, find all my data, gather all my data, catalog all my data, organize all my data.’ It sounds like a great way to spend $50 million and achieve nothing.”

Recent developments in AI have led to evolving roles within organizations, particularly the introduction of positions like chief artificial intelligence officer. It’s essential for these roles to be clearly defined with specific outcomes and responsibilities to avoid unnecessary bureaucracy. The goal should be to enable and empower these roles to drive value through AI technologies rather than expecting them to perform miracles due to their titles, Godden explained.

“I think the risk that we have with the chief AI officer is some of the same risk we’ve encountered with the chief data officer, which is we expected them to work magic because we created the position,” he said.  “I think what we need to make sure that we do is we define those is the why? What are they trying to affect? What is their responsibility that they have and have they been enabled to do that? By and large, I’m seeing organizations continue to struggle with that.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the CDOIQ Symposium:

Photo: SiliconANGLE