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Fivetran predicts data lakes, AI focus in 2025 trends

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Fivetran has outlined key predictions for the data management industry in 2025, emphasising the roles of data lakes and open file formats in supporting AI advancements.

The company discussed the heightened focus on AI investments in the coming years. Many organisations are keen on adopting AI, yet poor data management remains a significant barrier, resulting in issues like data inaccuracies and biases, which limit AI's potential. Taylor Brown, Chief Operating Officer and Co-Founder of Fivetran, remarked on this trend, stating: "AI models require large amounts of clean, high-quality data to function effectively and produce accurate results."

Another significant prediction by Fivetran is the increased reliance on data lakes to support AI initiatives. With the rising amount of unstructured and semi-structured data from sources such as IoT devices and social media, traditional databases will face challenges managing this influx. According to Fivetran, data lakes, supported by open file formats like Iceberg or Delta Lake, will provide the necessary scalability and flexibility for building accurate AI models.

Fivetran highlights the importance of automation in data ingestion and management as businesses increasingly depend on data lakes. Their Managed Data Lake Service aims to facilitate this transition by automating data ingestion and governance, allowing companies to expand their AI capabilities without the complexities of manual data management.

Data governance is expected to become a strategic business priority in 2025. With growing data volumes, organisations will focus on establishing robust governance frameworks to ensure data quality, compliance, and security. The cost-effectiveness of compute and storage offered by data lakes will further drive their adoption.

The proliferation of open file formats is another anticipated trend. These formats are expected to become industry standards, offering businesses the ability to future-proof their data architectures and avoid vendor lock-in. Fivetran positions its automated data integration capabilities as vital in supporting the shift towards these formats, enabling efficient data movement across diverse sources for AI and analytics applications.

Taylor Brown commented on the importance of integrating user-friendly tools for centralising data, noting: "Enterprises will increasingly leverage user-friendly data integration tools to centralise data from various operational data stores to create a corpus for AI training."

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