Using BigQuery object tables, we analyze unstructured Cloud Storage data with generative AI models and join the results with BigQuery structured data.

Managed disaster recovery in BigQuery offers automated failover of compute and storage to a different region and a new cross-regional SLA.

Organizations are challenged today to become both more data driven and more nimble to adapt quickly to changing conditions. These challenges are the driving forces behind much of their digital transformation or “modernization” efforts.

Snowflake Cortex is a fully-managed service that enables access to industry-leading large language models (LLMs) is now generally available. You can use these LLMs in select regions directly via LLM Functions on Cortex so you can bring generative AI securely to your governed data. Your team can focus on building AI applications, while we handle model optimization and GPU infrastructure to deliver cost-effective performance.

Accelerate Healthcare and Life Sciences is a one-day virtual event, featuring technology and business leaders from Elevance Health, Ginkgo Bioworks, Datavant and more, to discover executive priorities, best practices and potential data and AI challenges that are top of mind for 2024.

Since Snowflake’s Dynamic Tables went into preview, we have worked with hundreds of customers to understand the challenges they faced producing high-quality data quickly and at scale. The No. 1 pain point: Data pipelines are becoming increasingly complex. This rising complexity is a result of myriad factors.

Snowflake is dedicated to providing customers with intuitive solutions that streamline their operations and drive success. As part of our ongoing commitment to helping customers in this way, we’re introducing updates to the Cost Management Interface to make managing Snowflake spend easier at an organization level and accessible to more roles.

Unlocking the power of AI within SAP for your team requires overcoming a significant hurdle: data accessibility. SAP data’s complexity, spread across various modules, creates silos of information that your team might struggle to understand and utilize effectively. Inaccessible or misaligned SAP data will hinder your AI system’s ability to learn and deliver valuable results specific to your organization.

Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.

Watch how to use a multimodal LLM such as Gemini to analyze data in a BigQuery data lake and automatically generate schema layouts.