Data teams often face the challenge of delivering customized insights to business units with unique and specific needs. These groups typically have deep domain expertise and a clear understanding of their data requirements but lack the SQL skills or technical resources to create the necessary data subsets themselves. This creates a bottleneck, as data teams must step in to bridge the gap, leading to inefficiencies and delays.
Gigasheet Enterprise eliminates this friction by empowering non-technical users to interact directly with Snowflake data, enabling them to define and save their own views without writing SQL or engaging in complex processes. By leveraging Gigasheet’s spreadsheet-like interface and powerful Live Query functionality, users can filter, segment, and explore data on their own, saving significant time for both business users and data teams.
Snowflake views saved with Gigasheet adhere to existing data governance policies within Snowflake. Permissions, role-based access controls, and security protocols are all respected, ensuring that users work within the boundaries of organizational compliance. This allows teams to deliver the agility business units need while maintaining control and oversight over how data is accessed and used.
With Gigasheet Enterprise, organizations can improve collaboration, reduce burden on analytics resources, and enable a scalable, governed self-service analytics approach for Snowflake.
Live Query: Direct Access Without Data Replication
Gigasheet’s Live Query functionality connects directly to your Snowflake data warehouse, eliminating the need for data replication. When a user interacts with the dataset in Gigasheet’s spreadsheet-like interface, the platform queries the data live from Snowflake. This ensures users are always working with the most up-to-date information while reducing the complexity and cost associated with duplicating data.
Simplifying Custom Segmentation
Imagine you’re on the data team of an e-commerce company selling electronics. You have a large customer dataset of some 100 million+ rows stored in Snowflake. Various business units require reports and dashboards, each with unique segmentation criteria.
Instead of the back-and-forth communication prone to misinterpretation and errors, Gigasheet allows business users to create these segmentations directly.
Using Gigasheet, users can interact with their Snowflake data as if it were a spreadsheet. They can:
- Filter by Specific Attributes: For instance, users can set filters to segment customers from the United States born between 1950 and 1960.
- Build Complex Filters: The interface supports advanced, nested filters for more nuanced segmentations.
- Visualize Data Immediately: As users configure filters, the dataset updates instantly, providing clear visibility into the applied logic.
The result is a precise subset of data tailored to the needs of each business unit.
Saving the View Back to Snowflake
Once the desired segmentation is complete, the Gigasheet user can save it directly back into Snowflake as a secure view. This feature is designed to streamline workflows between business users and the data team while maintaining governance and control over the data.
To enable this functionality, the data team must first configure Gigasheet to allow post-back capabilities to Snowflake. This setup ensures that only authorized users can create and save views in Snowflake, adhering to organizational policies and maintaining data security. By implementing these controls, the data team retains oversight of how data is accessed and written back to the warehouse, preventing unauthorized changes or potential disruptions to existing systems.
After the setup is complete, the process for business users is simple and requires no coding. They can:
- Assign a Name to the View: Choose a descriptive name for the view, such as
Customer_Segment_USA_1950, to make it easily identifiable within Snowflake. - Push it Back to Snowflake: With a single click, the view is sent to Snowflake as a secure view object.
The newly created view appears in Snowflake alongside other database objects, and because it is a live view, it dynamically updates as new records are added or existing ones are modified in the underlying dataset. This ensures that users always have access to the most current data without requiring manual updates or additional intervention from the data team.
This approach allows Gigasheet users to directly contribute to data workflows while enabling data teams to manage permissions, maintain compliance, and ensure the reliability of the data environment. It’s a win-win, reducing bottlenecks for both business users and data engineers while keeping the system secure and governed.
Accessing the View in Snowflake
In Snowflake, the new view appears alongside other database objects. Because it’s a live view and not a static dataset, it dynamically updates as new records are added or existing ones change in the underlying table. This ensures consistency and accuracy without requiring manual updates.
The Benefits
- Empowering Business Users: Gigasheet eliminates the need for SQL expertise, enabling users to take ownership of their data requirements.
- Saving Data/Analytics Team Time: By offloading segmentation tasks, data teams can focus on strategic initiatives.
- Maintaining Data Freshness: Saved views in Snowflake remain updated in real-time, ensuring consistency and accuracy.
- Improved Collaboration: Non-technical users can contribute directly to the data workflow without reliance on IT or data engineering teams.
With Gigasheet, businesses unlock a powerful self-service analytics capability, allowing users to interact with Snowflake data in an approachable way. Instead of relying on pre-defined dashboards or waiting for data team resources, business units can now create, refine, and operationalize their own views of the data—streamlining workflows and driving better outcomes.
Ready to simplify your Snowflake workflows? Try Gigasheet for Snowflake today.
The ease of a spreadsheet with the power of a data warehouse.
