The data and artificial intelligence (AI) landscape continues to evolve, driven by strategic changes and technological advancements. Experts from Starburst and EncompaaS weigh in on the trends expected to shape the sector in 2025.
Justin Borgman, co-founder and CEO of Starburst, highlights the growing priority businesses are placing on real-time analytics. He says delivering insights in minutes is crucial to meeting customer demands and staying competitive, transforming traditional analytics from a reactive tool into a proactive business driver. This improvement enables faster decision-making, empowering departments ranging from marketing to customer service.
Borgman also foresees the acceleration and scaling of AI workflows through well-defined data products. The importance of data quality and governance, coupled with the business context, is becoming increasingly vital for AI applications. In this changing landscape, Lakehouse’s hybrid model is expected to gain traction. It seamlessly merges cloud and on-premises data storage, providing scalability and secure control, thereby providing a flexible and robust infrastructure for data management.
Furthermore, the resurgence of SQL in data lakes is remarkable. As technologies like Apache Iceberg simplify data access, SQL engines are taking advantage of Spark, improving accessibility and democratizing the use of data in organizations. This resurgence allows for broader control of data and allows teams to make informed decisions.
Traditional data warehouses are at risk of being eclipsed by modern data-driven SaaS applications built on lakes. According to Borgman, the total cost of ownership (TCO) of data lakes, without vendor lock-in, makes them an attractive option for margin-driven SaaS businesses. This infrastructure supports open formats and engines, providing a cost-effective and scalable solution.
On the other hand, Jesse Todd, CEO of EncompaaS, looks back on the transformation that AI has made in 2024, evolving from theoretical concepts to practical applications. He notes that organizations, learning from past successes and failures, have shifted their focus from document generation to data quality and security.
Todd observes that businesses now understand the transformative potential of AI, highlighting the need for proactive data preparation. As AI tools become more accessible and robust, they drive productivity and efficiency, allowing organizations to effectively leverage AI’s capabilities.
By 2025, Todd predicts that AI will disrupt core business processes rather than remaining a peripheral function. AI should be integrated into core operations, improving internal business outcomes. This transition from novelty to necessity sees AI becoming a fundamental part of information management.
In the coming year, the availability of AI services is expected to expand, allowing organizations to manage and use data more effectively. As businesses gain a better understanding of their data, they can ask more sophisticated questions, leading to strategic decisions and improved business processes.
The ideas shared by Borgman and Todd highlight a crucial shift toward data-driven business models and AI integration. These developments not only reflect changing technology trends, but also signify profound changes in organizational strategies as businesses strive to remain competitive and innovative in a rapidly evolving digital landscape.
