Snowflake is a cloud-based data warehousing tool that supplies companies with flexible and scalable storage while simultaneously hosting solutions for business intelligence.
The platform is built completely on the cloud and employs a subscription-based model which provides both storage and computation services that operate independently. Snowflake stores both structured and semi-structured data, converting it into a usable format that is compatible with SQL. The company’s services are provided on-demand, empowering users to select only the computational capacity and storage they need before paying for it based on usage or at monthly fixed rates.
Additionally, Snowflake uses a flexible system of cloud servers that decentralizes data and allows for each stakeholder or group within an organization to access the specific data sets they need without requiring complicated data transfers.
The company’s use of Amazon’s S3 servers and virtual warehousing means users can quickly query data without affecting the underlying set and receive closer to real-time data.
The company’s flexible payment structure also means that computation (which is charged per second, with a 60 second minimum) and storage can be activated for specific instances and projects without incurring long-term costs.
What Can I Use Snowflake For?
Snowflake’s scalable architecture and lightweight querying make it an ideal tool for companies that are starting their exploration of the data-driven model.
The platform’s usability factor and flexibility make it a valuable tool for companies that are seeking to test new systems, create their own analytical models, and try out different approaches to fulfill their data analysis and business intelligence needs.
One good use case for businesses who require periodic analysis is the use of ad-hoc models, which lets users create their own queries for specific instances. In these cases, Snowflake’s use of virtual warehouses allows stakeholders to create their own databases with live and cached data, making for faster queries and more current BI insights.
Additionally, Snowflake can connect to systems that use data lakes and create a layer that allows anyone to quickly access the system and explore the data without affecting the overall structure and modifying any existing data structures. By utilizing virtual warehouses and on-demand computation, users can explore smaller subsets of large data sets and view information as it arrives instead of querying static data that may already be out of date.
Snowflake Data Connector