Building Data Products Faster with Sigma, Snowflake and dbt

Building a robust data application continues to be a complex and iterative process. In a typical data application development lifecycle, data analysts work with business users to identify data requirements, which data engineers use to build usable data models and dashboards. As business users leverage these dashboards for their day-to-day analysis, new requirements inevitably surface, creating constant rework. Sigma significantly shortens the development lifecycle and reduces rework by bringing all parties to a clear understanding of what is required. Through collaborative and easy exploration of raw data without the upfront need to build a formal data model, data engineers can leverage this knowledge to build the formal data model right the first time. In this webinar, we demonstrate how Sigma, Snowflake and dbt come together to make this possible.