Sisense Data Connector for Connecting Live to Snowflake


Sisense connects directly to the Snowflake data warehouse using a connector officially certified by Snowflake to deliver an optimized customer experience, flexibly delivering access to all of your present and future data for detailed data exploration and insights. Sisense’s Elastic Data Engine provides the flexibility to prepare, query and manage data within Snowflake using both code and a web-based, visual data modeling experience.

Organizations can harness the power and elasticity of Snowflake by using Sisense’s advanced data pipelines, SQL-based materialized views and live data models to power complex ad-hoc analysis, dashboards and analytic apps.

Snowflake & Sisense’s Elastic Data Engine Features:

  • Securely connect and ingest data into Snowflake to create a single store for your data using SQL, Python and R
  • Explore both modeled and raw data to easily answer complex and ambiguous business questions without having to rebuild any upfront models
  • Optimize raw data stored in Snowflake with materialized views that further powers self-service analytics and query performance from Snowflake 
  • Connect, prepare and combine together dozens of tables directly in Snowflake into a single live model that can be accessed, queried and reused by all users across multiple dashboards
  • Mashup data into a cached data model from Snowflake with other data that has not, or can not be migrated, to Snowflake due to data ownership, regulatory or other concerns 

Sisense enables organizations to integrate with Snowflake’s existing systems of record and authentication systems to ensure users have adaptive governance to support the distribution of data to any organizational policy. Multi-level security from a system, object, role, and row-level that can be programmatically automated ensures to ensure organizations can quickly scale the integration between Snowflake + Sisense. 

Getting Started

To start using the Snowflake Connector, simply follow the instructions here.

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