Originally known as a cloud database, Snowflake has rebranded itself as an AI-powered data cloud, enabling businesses to integrate artificial intelligence into their data processes. During the Sydney segment of the Snowflake World Tour, company executives emphasized this strategic shift. Snowflake now serves more than 10,000 customers and partners, running over five billion jobs daily, and functions as both a data platform augmented by AI and a platform for developing AI-driven applications. According to CEO Sridhar Ramaswamy, this transformation simplifies data processing by leveraging natural language interfaces.
Ramaswamy underscored the benefits of Snowflake’s efficiency, suggesting that complexity in data management drives up operational costs. Snowflake’s model aims to reduce this complexity by offering an intuitive, pay-as-you-go platform, reducing the need for highly specialized staff. Further, the platform includes tools to manage and govern spending effectively, making it cost-efficient for diverse workloads.
One of Snowflake’s notable Australian clients, hardware retailer Bunnings, exemplifies its impact on business operations. Genevieve Elliott, Bunnings’ CIO, shared that the company envisioned a streamlined enterprise data platform capable of securely managing data for both employees and customers. With Snowflake at the core, Bunnings can now surface data across various applications, from PowerBI and Microsoft Excel to mobile apps and core business systems. This system has enabled Bunnings to shift from producing a single digital catalog to offering 300,000 personalized variations tailored to customers’ past purchases and engagement.
Another practical application involves weather-driven, localized merchandising. Elliott explained that while Bunnings has always recognized the influence of weather on customer purchasing, its data science team has now quantified this relationship. By integrating historical weather data with sales information by store, product, and hour, Bunnings can generate customized weekly merchandising plans within hours instead of days. Looking forward, the company aims to enhance employees’ data fluency and expand self-service data models to meet growing demand for insights.
Snowflake also prioritizes data governance, ensuring secure and efficient access to data. The Snowflake Horizon governance system helps organizations manage data access, protect sensitive information, and enhance data discoverability. Scalability, security, and cost concerns led Coles, another Australian client, to transition from an on-premise data platform to Snowflake’s cloud-based solution. Saurav Sachdev, Coles’ head of data, highlighted that with executive support for security and governance, the migration process has proceeded without hindrance. Coles is currently focused on improving efficiency through automation, freeing up resources for innovative projects like personalized customer experiences.
Judo Bank offers another example of Snowflake’s transformative potential. Despite only obtaining a license in 2018, the bank’s SQL Server-based system rapidly reached its capacity. After evaluating various options, Judo chose Snowflake and migrated approximately 1,400 workloads in just two months, largely due to internally developed automation tools. The migration has streamlined operations, reduced management demands, and improved data-sharing capabilities. Governance enhancements have also led to significant cost reductions, with Judo’s monthly expenses dropping from A$8,500 to A$315 for the same workloads. The bank’s data team continues to harness these efficiencies to deepen customer insights.
Snowflake’s adaptability is particularly appreciated by large institutions like the Commonwealth Bank of Australia (CBA), which uses the platform for diverse tasks ranging from real-time fraud detection to personalized customer offers. Chief Data and Analytics Officer Andrew McMullan praised Snowflake’s Data Exchange feature, which enables data sharing without duplicating data. This capability has allowed CBA to partner with organizations like the Bureau of Meteorology to deliver critical notifications to customers during natural disasters. The bank also uses Snowflake to offer its NameCheck service, which aids in fraud prevention by verifying account names and identifying suspicious accounts. CBA is now exploring a large language model to simplify data accessibility and reduce dependency on legacy applications.
Snowflake supports generative AI projects through its Cortex service, a fully managed platform providing access to foundational AI models. Snowflake’s director of product, Jeff Hollan, highlighted that Snowflake Cortex enables companies to train smaller, cost-efficient models tailored to organizational needs. This capability supports businesses in applying AI strategically, without the technical complexity often associated with model development.
Accenture’s senior managing director for Asia-Pacific data and AI, Vivek Luthra, identified financial services as a leader in AI adoption within the region. He advocates for scalable AI models that deliver measurable business value. Over the next few years, Luthra suggests that organizations refine AI models with their own data to support autonomous processes. Bunnings’ Elliott echoed this perspective, emphasizing that a robust data strategy is essential for successful AI deployment.
Snowflake’s comprehensive data cloud positions it as a valuable partner for organizations looking to integrate AI with data, streamline operations, and achieve data-driven growth. With flexible, secure, and cost-efficient solutions, Snowflake is proving its potential as a foundation for digital transformation in Australia and beyond.
