How AI and data analytics drive demand for relevant business data

The increasing demand for relevant business data is being fueled by the rise of AI and data analytics, both of which face challenges in accessing and utilizing high-quality data. With the proliferation of AI models and advancements in AI hardware, businesses are eager to leverage AI's potential, but they are hindered by fragmented data architectures that create silos and impede timely access to data. Traditional architectures like data warehouses, data lakes, and data lakehouses all have limitations in effectively managing and sharing data. The open hybrid lakehouse model offers a promising solution by combining the strengths of these architectures, allowing for efficient data access, near real-time data ingestion, and secure sharing via data products. This approach enables businesses to maintain control over decentralized data while optimizing data quality for analytics and AI applications, ultimately unlocking significant business value in a rapidly evolving landscape.