Antoine Roex, OAKland Group
As we enter 2025, companies need to adapt their data strategies to incorporate advances in artificial intelligence and strengthen data governance. This article explores the emerging trends that will shape data management in the years to come.
Increased integration of artificial intelligence into data infrastructures
By 2025, artificial intelligence (AI) will play a central role in the transformation of data infrastructures. Companies will massively adopt big language models to improve data integration and automate analytical processes. Data fabric architectures will become the norm, facilitating data access and management across heterogeneous environments.
This evolution will enable better management of unstructured and semi-structured data, improving companies’ ability to respond rapidly to market changes.
Strengthening data governance and quality
Data governance will become an essential strategic function, over and above regulatory imperatives. Companies are investing in data observability solutions to monitor and ensure the quality of data flows in real time. This approach will guarantee high standards of accuracy and reliability of data used for advanced analysis.
Reinforced governance will also make it possible to measure the impact of data investments on business value creation.
Adoption of augmented analysis and real-time processing
Companies are increasingly integrating augmented analytics, where AI facilitates data preparation, insight generation and interpretation. This trend will make complex analytics accessible to a greater number of users, fostering a data-driven corporate culture.
At the same time, the need for responsiveness to the massive volumes of data being collected will drive companies to invest in real-time data processing, essential for responding to customer needs and optimizing operations on an ongoing basis.
Convergence of software engineering and data science skills
The boundary between data teams and software development teams will become increasingly blurred. AI projects will require a solid understanding of software engineering principles, while software engineers will need to master the fundamentals of data science. This convergence will facilitate the creation of robust, operational data products, integrating best practices in project management, version control and agile development.
This cultural and organizational change will be crucial to meeting the demands of large-scale data projects.
Conclusion
Data strategy trends for 2025 point to increased AI integration, strengthened governance and a more flexible data infrastructure. Companies that anticipate and embrace these developments will be better positioned to exploit the full potential of their data and maintain their competitiveness in the marketplace.
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