From Zero to Snowflake: How to Get Your Business Started with AI Data Cloud

On Wednesday, September 10th, together with Snowflake, Seven Peaks hosted “From Zero to Snowflake: How to Get Your Business Started with AI”, a workshop for business professionals and data specialists eager to understand how AI can transform the way organizations use data. Speakers included Rene Wong, Partner Manager, ASEAN, and Pearline Vijayakumar, Partner Solutions Engineer, APJ Growth Partners, from Snowflake, along with Damien Velly, VP of Data and Analytics at Seven Peaks. They shared the following insights on taming data chaos, embedding AI directly into workflows, and unlocking new opportunities for modern data teams.

Taming Data Chaos with a Unified Platform

A common hurdle for businesses today is managing data spread across different systems and formats. Snowflake addresses this with its AI data cloud, a single platform for all types of data, from structured to unstructured, including open-source options like Apache Iceberg tables.

The platform is built for flexibility. You can use your preferred cloud provider, whether it's AWS, Azure, or GCP, and connect data across multi-cloud setups. As a fully managed service, Snowflake handles all backend maintenance, which frees up your teams to focus on loading data and running workflows. It also allows developers to work in familiar languages like Python, Java/Scala, and SQL within a secure and governed environment.

Putting AI to Work on Your Data

Once your data is organized, the next step is extracting value from it. Snowflake’s Cortex AI uses natural language to answer questions and can even perform actions like drafting emails based on your data. It can handle messy information, understand business context, and integrate with leading LLMs like GPT, Claude, and Llama directly through SQL or APIs.

This technology is the foundation for creating intelligent applications on the Snowflake platform. For example, Snowflake Intelligence uses data agents to interact with diverse organizational data, connect to external applications like Salesforce, and provide accurate answers based on a semantic model that understands complex business terms.

The platform’s compute resources, called virtual warehouses, are scalable and operate on a consumption-based pricing model, so you only pay for what you use. Users can set budgets and automatically suspend warehouses to control costs effectively.

Advanced Features for Modern Data Teams

Snowflake’s features are designed for real-world development, including ingesting and transforming data from external sources, such as parsing specific details from JSON arrays. These are some of its standout features.

• Zero-copy cloning allows you to create a dev version of a table instantly without using extra storage. You can experiment by adding columns or cleaning data, and the changes won't affect the original table until you decide to swap them.
• Time travel is a powerful data recovery feature that lets you access and restore historical data or recover accidentally deleted tables. The Standard edition offers one day of history, while the Enterprise edition provides up to 90 days. It also includes the ability to recover accidentally dropped tables with a simple “undrop” command.
• Data sharing provides you with access to your data across multiple geographic locations, or even monetizes your data, all without losing your data residency or compromising data protection with a data clean room.
• On the data marketplace, you can easily find, try, or buy data, apps, and AI products from some of the world's leading companies.

Embedding AI directly into your workflow

Snowflake’s Cortex Playground is a central hub for using AI models. The most practical feature for many teams is its set of AI-powered SQL functions, which allow you to embed Snowflake AI directly into your queries. Below are some of the notable examples.

Determine text sentiment with AI_SENTIMENT

Analyze text data to understand the emotional tone, classifying it as positive, negative, or neutral. It’s a great tool for customer feedback analysis, social media monitoring, and brand perception studies.

Categorize data with AI_CLASSIFY

Automatically sort different data types, including text, images, or audio, into predefined categories. This function is helpful for organizing unstructured data, content moderation, and intelligent routing of information.

Generate executive summaries with AI_SUMMARIZE_AGG

Create concise and informative summaries from large datasets. This function is especially useful for executives and leaders who need quick overviews of complex reports, meeting transcripts, or extensive research documents.

Extract specific answers from text with EXTRACT_ANSWER

Pinpoint and retrieve specific answers to questions embedded within textual data. This function accelerates information retrieval from legal documents and research papers to customer service interactions.

These tools make it possible for more users to apply AI without needing specialized knowledge, turning complex data into clear, actionable results.

Start Your Project with a Clear Strategy

If you need help building an effective Snowflake-powered AI data cloud strategy, our team is here to help. As a Snowflake partner, Seven Peaks can deliver the infrastructure you need to make informed decisions and drive measurable results. Contact us today.

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