Key Takeaways

• “The most common roadblocks to the success of D&A initiatives are all human-related challenges, such as skills shortages, lack of business engagement, difficulty accepting change and poor data literacy throughout the organization.”

• “D&A leaders are still not speaking the language of business, but we’re under intense pressure to demonstrate the value of our initiatives to other business peers and executives.”

• “Much of what we do in D&A is strategy enablement, which by definition plays out over a longer period of time. We need a new way to talk about investments in D&A to show future impact and how they meet the needs of multiple stakeholders.”

• “Think about speaking the language of business. Now more than ever, D&A leaders must have a translation layer between their D&A initiatives and the organization’s mission-critical priorities.”

• “Make business stakeholders the hero in your business value story by meeting their KPIs and enabling their objectives by connecting them with data and analytics insights.” 

• “Culture is the reason we say we fail. Even the highest ranking executives in your organization can’t change the whole culture, but you can change the culture around you to a data-driven one.”

Key Takeaways

• “To prepare for the business opportunities and challenges of the digital era, D&A leaders should evaluate their current practices in accordance with the seven foundations for modern D&A governance.”

• The seven pillars of modern D&A governance are:

1. Aligning Data Governance Efforts with Business Outcomes

2. Accountability and Decision Rights

3. Implement Trust-Based Governance

4. Value Digital Ethics and Transparency

5. Consider Risk Management and Information Security 

6. Educate and Train on Governance

7. Encourage Cultural Change and Collaboration

• “Trust-based D&A governance is essential since some D&A assets are created, consumed, and controlled in a distributed environment.”

• “A D&A governance model should operate in an open and transparent manner, based on a clear decision-making process and ethical foundations.”

• “D&A governance is not something that sits apart from an organization’s D&A strategy and operating model, rather it plays a critical role in it.”

• By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.

Key Takeaways

• By 2027, organizations investing in AI will process 60% of IT and digital initiatives to the approval stage without human intervention.

• By 2025, 55% of IT departments will adopt data ecosystems, which will consolidate the vendor landscape by 40%, reducing cost while reducing choice. “The data ecosystem consists of an end-to-end set of integrated tools that simplify and reduce the time required to develop applications for all data use cases.”

• By 2025, 75% of data will be generated outside of these centralized facilities. “Currently, most enterprise data is generated in centralized data centers or cloud regions, however, this pattern will dramatically change in the future.” 

• “Applications, AI training, and inference will need to move closer to edge environments near IoT endpoints as the need for processing data at the point of creation grows.” 

• By the end of 2025, there will be 11.7 billion IoT devices and their capabilities will expand as compute, security and bandwidth technology evolves. “This will create a rich foundation for edge analytics capabilities to be widely available.”

• By 2024, 60% of intelligent software-as-a-service (SaaS) will be composed from packaged business capabilities providing data, analytical insight and operational application services. “Generative AI is an emerging technology that has only begun to be exploited commercially.” 

• By 2025, the concentration of pretrained AI models among 1% of AI vendors will make responsible AI a societal concern. “Adopt a risk-proportional approach to deliver AI value.”