SNOWFLAKE
DATA & ANALYTICS
Organisations today face unprecedented volumes and varieties of data, often siloed across departments and platforms.
Traditional data warehouses – centralised systems designed to collect, store and organise data from multiple sources, optimised specifically for efficient reporting and analytical querying – struggle with scalability, performance and integration, limiting the ability to derive timely insights. But Snowflake was established to change everything.
Snowflake introduced a cloud-based data warehouse that separates storage and compute, enabling elastic scalability, high concurrency and seamless data sharing, regardless of cloud provider or region.
Its architecture allows companies to consolidate disparate data sources, process both structured
SNOWFLAKE
HEADQUARTERS: MONTANA, USA NUMBER OF EMPLOYEES: 6,800 REVENUE: US $ 50.3BN( 2025)
NUMBER OF COUNTRIES: 40 OFFICES WORLDWIDE and unstructured data and scale resources on demand without performance trade-offs.
Snowflake’ s approach to the data warehouse problem Snowflake’ s founding vision was to do for data warehouses what Amazon Web Services( AWS) did for data storage – harnessing the cloud’ s flexible computing as if it were one giant supercomputer, enabling customers to quickly and cost-effectively organise and analyse large amounts of data.
Snowflake’ s platform is built on top of cloud infrastructures like AWS, Azure and Google Cloud and supports multi-cloud environments.
Built for modern analytics, Snowflake’ s infrastructure supports everything from geospatial and predictive analytics to ML and Gen AI workloads.
The introduction of AI-powered assistants and advanced analytics functions empowers analysts and developers to generate deeper insights faster, while robust governance ensures data security and compliance.
“ AI is a platform change in the sense that it is a new way in which everybody else in the world is going to get to software, is going to get to applications,” says Snowflake’ s CEO Sridhar Ramaswamy.“ Once we had that realisation, out came a bunch of product consequences, which AI needs to be central to Snowflake. We need to make it super easy to both build applications, but also build the most important applications ourselves.”
114 June 2025