Snowflake Intelligence provides insights to all members, reduces downtime analysis time, and improves productivity.

Snowflake held a press conference for the launch of ‘Snowflake Intelligence’ on the 20th at the 2nd basement level of Spark Plus COEX.

The presentation that day was led by Lee Su-hyeon, Snowflake Evangelist.

As global companies accelerate their adoption of AI, voices are growing louder that a "robust data foundation" is key to a successful AI strategy.

Evangelist Lee Su-hyeon emphasized, “We have entered an era where AI can call other AI,” and “AI’s influence is expanding across all fields, including marketing, sales, and customer management.”

In fact, more than 90% of companies that have adopted AI give positive evaluations of its ROI achievement and productivity improvement.

On the other hand, still The reason many companies struggle to adopt AI is because of 'data'.

Complex data systems, difficulties in managing infrastructure, limitations in identifying data sources, and inadequate data governance were identified as major obstacles.

Structured data accounts for only 20% of the data held by companies, while unstructured data such as documents, images, videos, and audio account for 80%.

Without integrating such diverse data, it is difficult to realize the true value of AI.

Evangelist Lee Su-hyeon stated, “A successful data strategy is to integrate structured and unstructured data and use AI to process and combine them.”

Snowflake is revolutionizing data integration and utilization through its AI data cloud platform.

OpenFlow connectors, zero-copy bidirectional connectivity, and partnerships with SAP, Palantir, and others allow you to freely connect on-premises and cloud, and various data sources and types.

In particular, the boundaries of data architecture are breaking down as real-time data linking becomes possible through collaboration with Oracle.

Snowflake supports a variety of languages, including SQL, Java, and Python, as well as GPU computing environments, allowing developers to develop AI applications in a familiar way.

AI SQL capabilities allow you to easily build multimodal pipelines that combine structured and unstructured data, and even complex data analysis can be processed in just three minutes using only natural language commands and function calls.

Snowflake Intelligence has unveiled a UI that analyzes integrated data and provides insights based on natural language questions.

From the field to C-levelAnyone can easily use the bell, and structured data is processed through SQL analysis, and unstructured data is processed through search-based analysis.

In fact, Wolfspeed, a US semiconductor manufacturer, used this platform to reduce downtime analysis time from two hours to two minutes, increasing productivity by 98%.

Evangelist Lee Su-hyeon emphasized, “AI is not an option, but a necessity,” and added, “Data cloud platforms with innovative features such as structured and unstructured data integration, a developer-friendly environment, and enterprise intelligence agents are key to a company’s competitiveness.”