Why 2025 will redefine the data base: 11 expert predictions

If 2023 was all about AI-powered chatbots and search engines, 2024 introduced useful AI – tools that can plan and perform multiple operations on digital platforms. From It’s Devin the engineering achievements of Microsoft’s early trials are Copilot Visionthe innovations were varied, but only one remained: the need to maintain stable and reliable data.

As businesses lean toward advanced AI, a number of trends have changed the way data is managed, protected and used. Businesses are increasingly adopting multicloud, Open the dataand best practices to avoid vendor lock-in and gain flexibility. He also focused on unprocessed dataturning data markets into places to provide pre-trained AI models with proprietary datasets and software. At the same time, advances in vector and graph databases added new opportunities, and laid the foundation for what was to come.

Now, as the story of AI continues, industry leaders share predictions about how the tools that support this will evolve in 2025.

1. Multimodal virtual reality will power the intelligent data flywheel

“In 2025, businesses will fully embrace multimodal data and AI, changing the way they work and deliver(ing) value. At the core of this transformation is the ‘Intelligent Data Flywheel’ – a cycle where real data enables AI-driven insights, inspires innovation and continuous change. Dark information of the day now – images, videos, audio, and sensor outputs – can be the starting point for unlocking sharper predictions, intelligent detection and real-time transformations, leading to better understanding more and more flexible for business.

“With real-time flywheels, AI will identify problems, optimize processes and create intelligent solutions. Businesses will rely on AI assistants to ensure data qualityidentify information and design strategies, which enable human resources to focus on high-level tasks. This will redefine, accelerate innovation and transform businesses into stronger and smarter organizations. “

– Yasmeen Ahmad, MD of strategy and product management for data, analytics and AI at Google Cloud

2. Chill factor: A water-cooled data center

“As the scope of AI applications continues to grow, pioneering organizations are turning to water cooling to improve performance and energy efficiency. Hyperscale cloud providers and large enterprises will lead the way, using water cooling in new AI data centers which houses hundreds of thousands of AI accelerators, networks and programs.

“Enterprises will choose to put AI tools on-premises instead of building their own – in part to reduce the financial burden of developing, deploying and deploying AI tools at scale. Or, they will borrow power as needed. This deployment will help businesses use the latest tools.” without the need to install and use them themselves. This change accelerates the implementation of water cooling as an AI data solution.”

– Charlie Boyle, VP of DGX platforms at Nvidia

3. The explosion of data around the world to create a lack of storage

“The world is creating an unprecedented amount of information. In 2028, about 400 zettabytes will be produced, with a compound annual growth rate (CAGR) of 24%. However, data storage is expected to have a 17% CAGR – therefore (it is growing) much faster than the growth of the generated data. And it takes a whole year to make a hard drive. This disparity in growth will disrupt the global balance of supply and demand. As organizations begin to experiment with and successfully implement AI strategies, they will need to create more data center space and secure storage plans, and invest in both AI and data infrastructure – while balancing financial, regulatory and environmental challenges. .”

– BS Teh, EVP and chief commercial officer at Seagate Technology

4. AI industries will shift to PaaS

“In 2025, the AI ​​industry will have evolved beyond its original role of providing services as a service, providing compute, network, and storage services, to provide platform-as-a-service capabilities. Although the initial services were necessary to start the adoption of AI, the wave AI industry leaders will prioritize platforms that drive data interoperability and deliver lasting value. This change will be essential for AI industries to be sustainable and competitive over time.”

– Rajan Goyal, cofounder and CEO at DataPelago

5. Companies will use their large datasets but they want reliability

“For the most part, early AI applications have only used rudimentary models trained on human data. With advanced RAGs becoming more popular and products maturing to generate more structured data, programs that augment the amount of data for business operations will begin to generate real value. But the bar for these programs will be high. : Businesses will want reliability from AI software, not a whiz-bang show.

“Furthermore, AI companies that provide these types of content must play fair with publishers and content providers to secure the future of AI development. They must enter into licensing agreements with content providers to ensure that they are paid for the valuable data they provide. This needs to be done. soon, before all the lawsuits and blocking of the AI ​​creeps.”

– Sridhar Ramaswamy, CEO at Snowflake

6. Business agents will destroy contact data

“In 2025, businesses will generate terabytes of communications, such as emails, Slack messages, and Zoom documents, using agents that provide analytics, dashboards, and decision support tools.

“This will improve many jobs in the industry.”

– Nikolaos Vasiloglou, VP of research and ML at RelationalAI

7. Data governance and quality will be major barriers to successful and effective adoption of AI

“In 2025, data management, accuracy and privacy will emerge as the biggest obstacles to adopting effective AI. As organizations look at the growth of AI, the realization will occur that successful AI results depend on reliable data. Managing and processing large amounts of information, ensuring compliance and maintaining Businesses need to overcome these challenges by investing the basis of data platforms which enables coordinated management of different data sources.

“As a result, we will see a greater emphasis on the role of data managers and governance systems that support AI initiatives, as businesses realize that data insecurity has a significant impact on AI.”

– Jeremy Kelway, VP of engineering for analytics, data and AI at EDB

“In 2025, transparent data platforms will emerge as essential tools for large enterprises, enabling them to gain visibility into the performance of data assets, quality, pipeline health, financial management and user behavior to address governance and integration challenges. Using insights wrongly and enabling real-time information, these platforms will improve data reliability and improve performance in many industries.”

– Ashwin Rajeeva, cofounder and CTO at Acceldata

9. All praise the royal cloud

“In 2025, we will see a real push towards private and private clouds. We are already seeing the biggest hyperscalers pouring billions of dollars into building data centers around the world to provide this. This… the potential will take time to come to the Internet; in the meantime, demand will increase significantly due to regulations those coming mainly from the EU. Those with a flexible, flexible and cloud-based approach. Those with infrastructure fixed, fixed will put themselves behind.”

– Kevin Cochrane, CMO of Vultr

10. Ascent of edge data processing

“I’m watching the growth of edge computing, driven by the proliferation of 5G, which brings data processing closer to the source and reduces latency. This can help democratize AI. The question is, can we create good AI applications that run on mobile devices, maybe independent of cloud resources?

“If 5G is available to field professionals, they can use AI to help them in their work – whether it’s medical professionals providing medical care in disaster areas where 5G is available but no Wi-Fi, or engineers and scientists making on-site decisions. with AI and real-time computing.”

– Jerod Johnson, Sr. technology evangelist at CData

11. The protection of unaltered data will be of utmost importance

“Traditionally, data protection focuses on the most important data because this is the data that needs to be restored as soon as possible. However, the landscape has changed, with unstructured data growing to include 90% of all data generated in the last 10 years. A large area of ​​petabytes of unstructured data along with its spread and rapid growth makes it highly vulnerable to ransomware attacks Unchangeable from ransomware will be a defense mechanism, starting with moving cold, inactive data to unalterable storage where it cannot be changed.

“Until then, IT managers and administrators will look for consistent data management solutions that provide the power to protect, distribute and analyze and use data within AI – a challenge that is bound to grow as AI develops. In addition, they will need to create ways for users to services will search the company’s data, improve accuracy, monitor privacy and transfer data to AI and statistical reports.”

– Krishna Subramanian, founder of Komprise

Finally, 2025 promises major advances in data-intensive businesses, from multimodal data flywheels to autonomous clouds. However, problems such as data control and limited storage will continue. Success in this dynamic space will depend on balancing innovation with confidence and consistency, turning data into a sustainable competitive advantage.