Despite the transformative potential of AI, many financial planning and analysis (FP&A) 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.

Making operational decisions in a tight timeframe is critical to the success of an organization. Real-time data ingestion enables quicker data availability, in turn enabling timely decision-making. Real-time ingestion is foundational to our digital transformation at Discover Financial Services. As a senior manager leading the streaming and real-time data platforms at Discover, I don’t want to be in the data replication business manually.

A look at how to augment LLM results with retrieval augemented generation (RAG) and vector search, directly from BigQuery.

With integration to Vertex AI, you can use multimodal LLMs like Gemini Pro 1.0 and Gemini Vision Pro 1.0 in BigQuery to create marketing campaigns.

Earlier today, Qlik announced its expanded role as a Snowflake Cortex launch partner, and this article explains how the two solutions work together to benefit our customers. Let’s begin by quickly reviewing Snowflake Cortex.

For any product team with a Software as a Service (SaaS) application, the significance of embedding capable, reliable analytics is well understood. But it’s important to remember how valuable these tools are for your users’ experience, too. Having fast access to data and easy ways to explore it is, as you know, key to monitoring business performance, finding trends, sharing insights, and improving your core product. Today’s business user also wants more when they use your product.

On April 24, we released Snowflake Arctic with a key goal in mind: to be truly open. In line with that goal, the Snowflake AI Research team is writing a series of cookbooks to describe how to pretrain, fine-tune, evaluate, and serve large-scale mixture-of-experts (MoEs) such as Arctic.

The emergence of generative AI (gen AI) heralds a new, groundbreaking era for advertising, media and entertainment. According to a recent Snowflake report, Advertising, Media and Entertainment Data + AI Predictions 2024, gen AI is going to transform the industry — from content creation to customer experience. The companies that will come out ahead during this time are those that most successfully and quickly supercharge their data strategy.

The pharmaceutical industry generates a great deal of identifiable data (such as clinical trial data, patient engagement data) that has guardrails around “use and access.” Data captured for the intended purpose of use described in a protocol is called “primary use.” However, once anonymized, this data can be used for other inferences in what we can collectively define as secondary analyses.